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Are students with disabilities suspended more frequently than otherwise similar students without disabilities? ☆

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Students with disabilities (SWD) have been reported to be disproportionately suspended from U.S. schools and so more likely to experience the "school-to-prison pipeline" through suspension's associations with lower academic achievement, dropout, juvenile delinquency, and adult crim-inality. Yet few studies have estimated SWD's risk of more frequent suspension while simultaneously controlling for potential confounds. Negative binomial regression modeling of suspension count data from a nationally representative and longitudinal sample (N = 6,740) indicated that males, those from lower resourced families, and students attending more economically segregated schools were more frequently suspended. On average, students who are Black received about 1.6 times as many suspensions by the end of 8th grade as otherwise similar White students. In contrast, having a disability by 1st grade was not a risk factor for more frequent suspension by the end of 8th grade while simultaneously accounting for other risk factors (e.g., gender, race/ethnicity, family SES, prior history of externalizing problem behaviors, being from a English-speaking household, school-level economic composition). Students with specific disability conditions (e.g., emotional disturbances, speech or language impairments) were not at increased risk for more frequent suspension. Students with disabilities who are Black, Hispanic, or of other race/ethnicity were not more frequently suspended than SWD who are White.
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Journal of School Psychology
journal homepage: www.elsevier.com/locate/jschpsyc
Are students with disabilities suspended more frequently than
otherwise similar students without disabilities?
Paul L. Morgan
a,
, George Farkas
b
, Marianne M. Hillemeier
a
, Yangyang Wang
a
,
Zoe Mandel
a
, Christopher DeJarnett
a
, Steve Maczuga
a
a
The Pennsylvania State University, United States of America
b
University of California, Irvine, United States of America
ARTICLE INFO
Action Editor: Amy Briesch
Keywords:
Suspension
School-to-prison pipeline
Special education
Longitudinal
Racial/ethnic minorities
Disparities
ABSTRACT
Students with disabilities (SWD) have been reported to be disproportionately suspended from
U.S. schools and so more likely to experience the “school-to-prison pipeline” through suspension's
associations with lower academic achievement, dropout, juvenile delinquency, and adult crim-
inality. Yet few studies have estimated SWD's risk of more frequent suspension while simulta-
neously controlling for potential confounds. Negative binomial regression modeling of suspen-
sion count data from a nationally representative and longitudinal sample (N= 6,740) indicated
that males, those from lower resourced families, and students attending more economically
segregated schools were more frequently suspended. On average, students who are Black re-
ceived about 1.6 times as many suspensions by the end of 8th grade as otherwise similar White
students. In contrast, having a disability by 1st grade was not a risk factor for more frequent
suspension by the end of 8th grade while simultaneously accounting for other risk factors (e.g.,
gender, race/ethnicity, family SES, prior history of externalizing problem behaviors, being from a
English-speaking household, school-level economic composition). Students with specific dis-
ability conditions (e.g., emotional disturbances, speech or language impairments) were not at
increased risk for more frequent suspension. Students with disabilities who are Black, Hispanic,
or of other race/ethnicity were not more frequently suspended than SWD who are White.
1. Introduction
U.S. schools are systems for academically, behaviorally, and socially educating students. Schools are therefore expected to be safe,
orderly, and civil environments where criminal, violent, or threatening behaviors rarely, if ever, occur. Schools may use suspensions
to deter students from engaging in such behaviors. Specifically, suspension is designed to decrease the likelihood that violent or
seriously disruptive students continue to engage in potentially dangerous behaviors as well as to protect the safety and ensure the
education of other students (Lamont et al., 2013). Seriously disruptive students who remain in classrooms often adversely affect the
learning and behavior of their peers (Carrell & Hoekstra, 2010;Figlio, 2007;Fletcher, 2010;Gottfried, Egalite, & Kirksey, 2016;Horoi
https://doi.org/10.1016/j.jsp.2018.11.001
Received 11 April 2017; Received in revised form 22 October 2018; Accepted 28 November 2018
Funding support was provided by Spencer Foundation Midcareer Grant to the first author as well as an infrastructure grant (P2CHD041025),
Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health. No official endorsement should
be inferred.
Corresponding author at: Department of Education Policy Studies, 310E Rackley Building, The Pennsylvania State University, University Park,
PA 16802, United States of America.
E-mail address: paulmorgan@psu.edu (P.L. Morgan).
Journal of School Psychology 72 (2019) 1–13
0022-4405/ © 2018 Published by Elsevier Ltd on behalf of Society for the Study of School Psychology.
T
& Ost, 2015;Neidell & Waldfogel, 2010). About 7 million students, or about 14% of the school-aged population, were suspended from
U.S. schools in 2011–2012 (U.S. Department of Education, 2016a, 2016b).
Despite its use by U.S. schools, suspension is increasingly questioned as a disciplinary practice because of its possible adverse
effects on students who are suspended. For example, Morris and Perry's (2016) analyses of a longitudinal sample of students in
Kentucky indicated that suspended students tended to later display lower reading and mathematics achievement. Noltemeyer, Ward,
and Mcloughlin's (2015) meta-analysis of 34 studies indicated that suspended students were more likely to drop out of school. Use of
suspension may result in large fiscal costs for U.S. states through lost future tax revenue (Rumberger & Losen, 2016). Both cross-
sectional and longitudinal studies indicate that students who are suspended are more likely to engage in substance abuse and violent
behaviors as well as to be referred to courts during adolescence (Hemphill et al., 2009;Hemphill, Heerde, Herrenkohl, Toumbourou,
& Catalano, 2012;Nicholson-Crotty, Birchmeier, & Valentine, 2009). Students who are suspended are also more likely to later engage
in violent criminality and to be arrested in adulthood (Katsiyannis, Thompson, Barrett, & Kingree, 2013;Mowen & Brent, 2016). By
increasing the risk of academic difficulties, school dropout, substance abuse, juvenile delinquency, and adult criminality and arrest,
suspension is viewed as an entry point into the metaphorical “school-to-prison pipeline” in which school-based disciplinary practices
and policies increase the risk that students interact with the juvenile and adult incarceration systems (Hemphill et al., 2009;Mowen &
Brent, 2016). For example, being suspended from school is positively associated with committing crimes, including felonies, that
result in arrest and referral to the juvenile justice system (Cuellar & Markowitz, 2015;Mittleman, 2018).
1.1. Disparities in the use of suspension by U.S. schools
In addition to suspension's associations with lower academic achievement, dropout, juvenile delinquency, and adult criminality,
there is also suggestive evidence that U.S. schools may discriminate in their use of suspension. For example, students who are racial or
ethnic minorities have been reported to be more likely to be suspended than students who are White (Skiba et al., 2014;U.S.
Government Accountability Office [GAO], 2018). These disparities can occur even among otherwise similarly behaving students
(Horner, Fireman, & Wang, 2010;Petras, Masyn, Buckley, Ialongo, & Kellam, 2011), as well as those attending similarly resourced
schools (GAO, 2018). Racial disparities in suspension are thought to at least partially explain achievement gaps (Gregory, Skiba, &
Noguera, 2010;Morris & Perry, 2016). Males, students being raised in low-income households, as well as those who are older for their
grade level have also been found to be more likely to be suspended, including among otherwise similarly behaving students (Petras
et al., 2011;Theriot, Craun, & Dupper, 2010), thereby suggesting that U.S. schools may be discriminating against some socio-
demographic groups in their disciplinary practices (National Research Council [NRC], 2004). However, and alternatively, it may be
that school contexts partially explain these disparities, particularly for racial or ethnic minorities and those from low-income families
who more frequently attend schools where “zero tolerance” disciplinary practices are in use (Kinsler, 2011). Thus, what is attributed
to discrimination due to differential treatment of similarly situated students may instead result from minority students being more
likely to attend schools whose disciplinary practices involve greater use of suspension.
Students with disabilities (SWD) have also been reported to be disproportionately suspended (GAO, 2018;Sullivan, Klingbeil, &
Van Norman, 2013), leading to suggestions that schools may be discriminating in regards to disability status (Kim, Losen, & Hewitt,
2010;Losen & Gillespie, 2012). For example, suspension rates for students with and without disabilities are estimated to be about
12–15% and 6–7%, respectively (Achilles, McLaughlin, & Croninger, 2007;Losen & Gillespie, 2012;U.S. Department of Education
Office for Civil Rights [OCR], 2014). Analyses of cross-sectional data from multiple years suggest that the risk of suspension of SWD
began increasing around 2000 (Krezmien, Leone, & Achilles, 2006;Zhang, Katsiyannis, & Herbst, 2004), possibly as SWD began
spending more of their school days in general education classrooms due to mainstreaming (U.S. Department of Education, 2016a,
2016b). General education teachers have been shown to be more likely to self-report attitudes of concern, indifference, or rejection
towards SWD than towards students without disabilities (Cook, Cameron, & Tankersley, 2007;Cook, Tankersley, Cook, & Landrum,
2000). Among SWD, those identified as having emotional disturbances (ED), specific learning disabilities (SLD), or speech or lan-
guage impairments (S/LI) have been reported to be more likely to be suspended (Achilles et al., 2007;Krezmien et al., 2006;Sullivan
et al., 2013). Racial and ethnic minorities with disabilities have been reported to be especially likely to be suspended (Achilles et al.,
2007;GAO, 2018;Krezmien et al., 2006;Losen & Gillespie, 2012), and so to experience the school-to-prison pipeline (Behnken et al.,
2014). This may occur because of a lack of training in effectively managing the classroom behaviors of SWD, especially those who are
more likely to engage in behaviors that teachers view as disruptive or difficult to manage. This may also occur because of a lack of
cultural or language sensitivity in working with SWD who are racial or ethnic minorities (Mendez & Knoff, 2003;Zhang et al., 2004).
To limit the possibility that SWD who are racial or ethnic minorities are being suspended due to discriminatory discipline practices,
federal legislation requires U.S. states to monitor for significant disproportionality in the use of suspension by schools districts. Recently
enacted federal regulations expand this monitoring by requiring school districts to use a standard methodology when monitoring for
significant disproportionality in the use of suspension and other disciplinary practices (U.S. Department of Education Equity in IDEA
Rule, 2016b). These new federal regulations expand the manifestation determinations and other legal protections already provided
through the Individuals with Disabilities Education Act (IDEA) that ensure that schools continue to provide special education services to
SWD whose disruptive behaviors are related to underlying conditions (U.S. Department of Education Equity in IDEA Rule, 2016b). If
significant disproportionality in the use of suspension is found using the standard methodology for SWD who are racial or ethnic
minorities, school districts in the U.S. are required to review and revise the policies, practices, and procedures that contribute to the
disparities as well as reallocate their federal funding (U.S. Department of Education Equity in IDEA Rule, 2016b). Federal im-
plementation of these regulations was recently delayed pending further review, including regarding whether the disparities are due to
discriminatory practices or instead to other explanatory factors (U.S. Department of Education, 2018a, 2018b).
P.L. Morgan et al. Journal of School Psychology 72 (2019) 1–13
2
1.2. Limitations in the knowledge base regarding whether and which SWD are being disproportionately suspended
Current empirical evidence regarding the extent to which SWD, including those who are racial or ethnic minorities, are being
disproportionately suspended as they attend U.S. schools is currently limited in several ways (Mendez & Knoff, 2003). First, most
prior studies investigating whether SWD are disproportionately suspended have used limited statistical controls (e.g., year, race)
(Krezmien et al., 2006;Vincent, Sprague, & Tobin, 2012;Zhang et al., 2004) or cross-sectional designs (Anderson & Ritter, 2017;
GAO, 2018;Goran & Gage, 2011). Thus, the resulting risk estimates have been unadjusted for strong potential confounds (e.g.,
gender, age, family socioeconomic status [SES], prior behavioral or academic functioning). The risk attributed to having a disability
may therefore be partly—or fully—explained by other factors (Duran, Zhou, Frew, Kwok, & Benz, 2011;Theriot et al., 2010).
Second, very few studies have attempted to identify risk factors for more frequent suspension. Most of the available studies
instead have estimated the risk of being suspended dichotomously (i.e., “yes” or “no”) (e.g., Achilles et al., 2007;Bowman-Perrott
et al., 2013;Krezmien et al., 2006;Duran et al., 2011;Hemphill et al., 2009, 2012;Martin, 2014). Yet dichotomizing a variable that
could be measured continuously results in lost data, larger standard errors, reduced statistical power, and possibly biased risk
estimates (Altman & Royston, 2006;MacCallum, Zhang, Preacher, & Rucker, 2002). Identifying risk factors for more frequent sus-
pension is also substantively important. This is because students who are more frequently suspended are especially likely to ex-
perience (a) academic difficulties in school due to increased absenteeism and (b) involvement with the criminal justice system due to
less adult supervision and more opportunities to interact with criminally active individuals (Anderson & Ritter, 2017). Mowen and
Brent (2016) recently reported a strong relation between the frequency of suspension and children's risk of later arrest. Those who
were suspended across two, three, or four of the study's survey waves were 136%, 252%, and 400% more likely, respectively, to later
be arrested compared to those suspended only during one survey wave.
Third, and although a few available studies have used more extensive statistical controls, these studies have analyzed single
district- (Sullivan et al., 2013) or state-level (Anderson & Ritter, 2017;Kinsler, 2011) samples not designed to generalize to the U.S.
school-aged population. The few studies that have estimated the frequency of suspension among SWD find that those with the specific
conditions of SLD, ED, or other health impairment (OHI), as well as students who are Black, male, or from lower SES families are
suspended more frequently. However, generalizability of the samples and statistical control for potential confounds have been
limited. For example, Sullivan et al.'s (2013) analyses indicating that SWD were more likely to experience multiple suspensions were
based on data from a single, unrepresentative school district in Wisconsin where 50% of the parents had at least a college degree.
Further, the cross-sectional data available to the investigators meant that prior behavioral functioning could not be controlled for as a
potential confound. Limited generalizability and lack of control for potential confounds also characterize the study by Sullivan, Van
Norman, and Klingbeil (2014) that analyzed data from the same district in Wisconsin. Both of these studies examined a constrained
range of 0, 1, or > 1 suspensions. Neither Mowen and Brent's (2016), nor Petras et al.'s (2011), nor Mendez and Knoff's (2003)
analytical samples included SWD. Anderson and Ritter (2017) examined school-level but not individual-level risk factors for more
frequent suspension.
Because prior studies reporting on the suspension risk of SWD have been unable to adjust for prior behavioral functioning,
academic achievement, and other potential confounds (Sullivan et al., 2014), contrasts between otherwise similar students with and
without disabilities typically have not been possible. Yet contrasts between similarly situated students who differ in their disability
status would better evaluate whether schools are discriminating against SWD when using suspension (e.g., NRC, 2004;OCR, 2016).
The very few studies reporting estimates designed to generalize to the U.S. school-aged population, which might be expected to best
inform federal legislation and policy, have largely examined whether suspension risk varies by specific disability condition but only
among samples of SWD (Achilles et al., 2007;Bowman-Perrott et al., 2013;Duran et al., 2011). Thus, it is currently unknown
whether, among students who are otherwise similar in their behavior, academic achievement, and additional background char-
acteristics, schools suspend those with disabilities more frequently. It is also unknown how suspension frequency varies by specific
disability conditions as well as how disability status and race or ethnicity interact.
Establishing whether and to what extent SWD, including those who are racial or ethnic minorities, attending U.S. elementary and
middle schools are being more frequently suspended than otherwise similar students without disabilities has important implications for
federal legislation and policy as well as for educational research and practice. Doing so would better clarify whether, as hypothesized
(Losen & Gillespie, 2012) and thought to be occurring widely (U.S. Department of Education Equity in IDEA Rule, 2016b), U.S. schools
are discriminating against SWD in their use of suspension. This would be particularly important to examine for those SWD who are
racial or ethnic minorities. If SWD who are racial or ethnic minorities are being more frequently suspended than SWD who are White,
this would suggest the need for greater use of culturally and language sensitive behavioral interventions by school psychologists, special
education teachers, and other practitioners to better meet the specific academic or behavioral needs of students with special needs. More
broadly, such an investigation would help establish whether, as has been reported to occur for the specific condition of attention-deficit/
hyperactivity disorder (ADHD), being identified as disabled increases the likelihood of entering the metaphorical school-to-prison
pipeline for students who are racial or ethnic minorities through an attendant greater risk for suspension (Behnken et al., 2014). Finding
this to be the case would suggest that SWD who are racial or ethnic minorities may benefit from additional academic and behavioral
supports to avoid suspension's associated life-course adversities. Investigating which students with specific disability conditions are
more frequently suspended would also better inform federally mandated monitoring efforts.
1.3. Purpose of study
Given the aforementioned limitations of prior empirical work, the purpose of the current study was to evaluate the extent to
P.L. Morgan et al. Journal of School Psychology 72 (2019) 1–13
3
which SWD are being more frequently suspended as they attend U.S. elementary and middle schools. To address substantive and
methodological limitations in prior studies, we estimated the risk of being more frequently suspended using negative binomial
regression modeling of the number of times suspended by eighth grade from a nationally representative and longitudinal sample. We
statistically adjusted the risk factor estimates simultaneously for an extensive set of individual student-, family-, and school-level
covariates. Doing so should better approximate contrasts between similarly situated students and so yield rigorously derived esti-
mates of the risk for more frequent suspensions attributable to specific factors including disability status. We examined the following
research questions:
1. Are students identified as having disabilities by the end of first grade at greater risk of being more frequently suspended by the end
of eighth grade than students not so identified? Based on prior work (e.g., Sullivan et al., 2013), we hypothesized that SWD would
initially (i.e., in unadjusted estimates) receive more suspensions than students without disabilities.
2. To what extent is any initially observed risk of more frequent suspension for SWD explained by other student- (e.g., race/ethnicity,
gender), family- (SES), or school-level factors (racial, ethnic, and economic segregation), as well as plausibly exogenous individual
student-level behavior and achievement measured at school entry? Based on prior work investigating for potential discriminatory
disability identification practices by schools (Hibel, Farkas, & Morgan, 2010;Morgan, Farkas, Hillemeier, & Maczuga, 2017), we
hypothesized that other explanatory factors would fully explain initial but unadjusted associations between having a disability
and the frequency of suspension. We expected that these other explanatory factors would include individual student-level race or
ethnicity, gender, family SES, prior history of externalizing problem behaviors, difficulties with attention and other learning-
related behaviors, academic achievement, and school-level racial, ethnic, and economic segregation. We also hypothesized that
these alternative explanatory factors would explain the greater suspension risk previously reported for students with specific
disability conditions including SLD, ED, and S/LI (Bowman-Perrott et al., 2013;Sullivan et al., 2014).
3. Are SWD who are racial or ethnic minorities suspended more frequently than SWD who are White? We hypothesized that other
explanatory factors (e.g., family SES, prior behavioral functioning) would also account for these interactions (Morgan et al.,
2017).
2. Method
2.1. Data and analytical sample
We analyzed data from the Early Childhood Longitudinal Study-Kindergarten Class of 1998–1999 (ECLS-K), a data set collected
and administered by the National Center for Education Statistics (NCES). The ECLS-K is a nationally representative, longitudinal
cohort of children who were followed from kindergarten entry through the end of eighth grade. A multistage, probability sampling
design was employed in which approximately 1300 public and private schools were sampled from 100 geographic regions. About 24
kindergarten students were recruited from each school. Data collection continued throughout elementary and middle school. Surveys
were administered in kindergarten, first, third, fifth, and eighth grade. The NCES provided sampling weights to account for attrition
across sample waves. The study's sample contained information on 6740 students who participated in the ECLS-K from kindergarten
through eighth grade. As described below, we used multiple imputation to account for missing data for this sample.
2.2. Measures
2.2.1. School suspension
The dependent variable of interest was the number of times a student had been suspended from school by the spring of eighth
grade. During the parent interview portion of the ECLS-K eighth grade assessment, each parent was asked the number of times his or
her child had received an in- or out-of-school suspension. This was reported by parents as a cumulative total regardless of the ages or
grades at which each suspension occurred. Because this survey was administered to parents during the spring of the student's eighth
grade year, we refer to this variable as the student's number of suspensions through eighth grade.
2.2.2. Disability status
School personnel reported whether an Individualized Education Program (IEP) was on file. We considered SWD as those students
with IEPs on file who were receiving special education services due to formally identified disabilities. Along with the study's cov-
ariates, we used disability status (as indicated by an IEP being reported on file at the school) to predict the number of times students
were suspended by the spring of eighth grade. To reduce the possibility of reverse causality (i.e., that suspended students missed
instruction and thus performed less well academically, leading to being identified as disabled, such that any relation between these
variables was due to suspension resulting in disability identification rather than vice versa), we conservatively measured disability
status as having been identified by the spring of first grade. We did so because students identified as disabled received this desig-
nation prior to the preponderance of the time period when they were likely to be suspended (i.e., second to eighth grade). Doing so
helped ensure that any significant relations between disability status and suspension frequency were most likely due to earlier
disability identification affecting later suspension frequency. Prior work has found that most suspensions occur during middle school,
followed by high school. Very few suspensions occur during elementary school, suggesting that even fewer occur by first grade
(Mendez & Knoff, 2003).
Students who had an IEP by the end of first grade (i.e., 6.8% of the study's sample) represented only a subset of all students who
P.L. Morgan et al. Journal of School Psychology 72 (2019) 1–13
4
had an IEP by the spring of eighth grade. However, and by restricting attention to students identified as having disabilities by the end
of first grade, we limited the possibility that any relations observed between disability status and suspension frequency were the
result of more frequently suspended students having been, as a consequence of suspension, identified as having disabilities. Further,
students with an IEP by first grade should have had more severe impairments due to their earlier identification and so displayed
greater academic or behavioral difficulties than students identified as having disabilities in the later grades. This made for a more
conservative test of whether disability status increased the frequency of suspension. This is because, if having a disability increased
the risk of suspension frequency, then student with more severe impairments should have been the most likely to be suspended more
frequently. Put another way, if suspension frequency was not elevated for SWD with more severe impairments, it seems unlikely that
suspension frequency would be elevated for SWD with less severe impairments. We also examined the risks of more frequent sus-
pension associated with specific disability conditions. These specific conditions included SLD, ED, S/LI, intellectual disability (ID),
OHI, developmental delay (DD), or other disability condition (ODC). We coded ODC as including the following rare disability
conditions: deaf-blindness, deafness, hearing impairment, orthopedic impairment, traumatic brain injury, and visual impairment.
2.2.3. Head Start
Participating in Head Start has been reported to increase the risk for suspension by middle school, although this risk may itself
result from children who participated in Head Start being more likely to later attend under-resourced schools (Aughinbaugh, 2001).
We, therefore, used participation in Head Start as a covariate when examining whether SWD were more likely to be frequently
suspended. Parents reported in the fall of kindergarten whether or not their child had been enrolled in federally sponsored Head Start.
We used a dummy variable for having been previously enrolled in Head Start (1 = yes, 0 = no).
2.2.4. Non-English-speaking household
Students with limited English proficiency have been reported to be at decreased risk of suspension (Anderson & Ritter, 2017).
Parents were asked about the primary language spoken in their home during the fall kindergarten survey. We coded those students
whose parents reported a primary language other than English as “1” and those students reported as using English as their primary
language as “0.” We used the kindergarten measure of this variable to help ensure that it was measured prior to the time period when
students were at risk for suspension.
2.2.5. Reading achievement
Greater academic achievement has been reported to decrease the risk for suspension (Arcia, 2006;Mizel et al., 2016). We ac-
counted for reading achievement as a covariate using the ECLS-K Reading Test administered during the fall of kindergarten. All items
were field-tested and psychometric properties of items were evaluated using item response theory (IRT) methods. Items assessed in
kindergarten consisted of basic skills such as print familiarity, letter recognition, beginning and ending sounds, and rhyming sounds.
The reliability of the IRT-scale Reading Test scores for the kindergarten assessment was 0.93 (Pollack, Atkins-Burnett, Rock, & Weiss,
2005). We used the fall of kindergarten measure of this variable to ensure that it was measured prior to when students were most
likely to be suspended.
2.2.6. Mathematics achievement
Mathematics achievement in kindergarten was measured by the ECLS-K Mathematics Test. As with the Reading Test, all items
were field-tested and their psychometric properties evaluated using IRT methods. The Mathematics Test's items during kindergarten
emphasized basic skills such as identifying numbers and shapes and counting objects. The reliability of the IRT-scaled Mathematics
Test scores in the kindergarten assessment was 0.92 (Pollack et al., 2005). As with the reading assessment, we used the fall of
kindergarten measure of this variable to ensure that it was measured prior to when students were most likely to be suspended.
2.2.7. Behavior
Engaging in problem behaviors, particularly externalizing-type behaviors like fighting or being disruptive, has been reported to
increase the risk for suspension (Mizel et al., 2016). Students are typically suspended due to recurrent acting-out behaviors (Skiba
et al., 2014). General education teachers completed the Social Rating Scale, a modified version of the Social Skills Rating System
(Gresham & Elliott, 1990) to rate an individual student's behavior in the fall of kindergarten. The teachers used a frequency scale to
rate how often the student displayed a particular social skill or behavior (i.e., 1 = never; 4 = very often). Items used for the Ap-
proaches to Learning subscale measured how well a student self-regulated his or her behavior while completing learning-related tasks
(e.g., attentive, task persistent, flexible and organized) in the classroom. Controlling for prior achievement, these learning-related
behaviors best predict later achievement (Duncan et al., 2007;Tach & Farkas, 2006). The split-half reliability for the Approaches to
Learning subscale was 0.89 (Pollack et al., 2005). The Externalizing Problem Behaviors subscale measures the frequency of acting out
behaviors (e.g., argues with the teacher, fights, shows anger, disturbs the classroom). The split-half reliability for the Externalizing
Behaviors scale was 0.90 (Pollack et al., 2005). As with the achievement measures, we used the kindergarten measures of learning-
related and externalizing problem behaviors to ensure that they were measured prior to when students were likely to be suspended.
2.2.8. Socio-demographic characteristics
Students who are Black or Hispanic have been reported to have a higher risk of suspension (GAO, 2018;Petras et al., 2011), as
have boys (Sullivan et al., 2013). Students from lower SES families have also been reported to be more likely to be suspended than
students from higher SES families (Hemphill, Plenty, Herrenkohl, Toumbourou, & Catalano, 2014). Children's age, race or ethnicity
P.L. Morgan et al. Journal of School Psychology 72 (2019) 1–13
5
(coded as White, Black, Hispanic, or other), and gender have also been reported to increase the risk for suspension (Mizel et al.,
2016). Data on these variables were collected from parents during the ECLS-K kindergarten interviews. Family SES was assessed using
a multivariate parental self-report questionnaire measuring maternal, paternal, and/or guardian education levels and occupations as
well as family income at each of the survey waves. Because our dependent variable was the cumulative number of suspensions
received by the spring of eighth grade, we used the SES measure as experienced by students over this time period. Accordingly, we
followed the common practice of averaging these variables across the survey waves.
2.2.9. School characteristics
Attending a racially or economically segregated school has been reported to increase the risk of suspension (Hughes, Warren,
Stewart, Tomaskovic-Devey, & Mears, 2017). We therefore included covariates that captured information about the socio-
demographic composition of the schools that students attended including the percentages of students who were Black or Hispanic and
those eligible to receive free lunch. We averaged these variables across the survey waves so that each represented the combined
school-level racial and economic conditions experienced by the study's students.
2.3. Analysis
We first descriptively examined the data including calculating the percent with different numbers of times suspended for students
with and without IEPs by first grade. We then used negative binomial regression to model the number of times students were reported
to have been suspended. Allison (2012) recommends use of negative binomial regression models when examining count data. This is
because, unlike Poisson models that often fit count data relatively poorly, negative binomial regression models allow for over-
dispersion (e.g., as here, where most students never experienced suspension and so there were a very large number of zero counts),
while also often being easier to estimate than zero-inflated Poisson models. Negative binomial regression also allows for greater
flexibility when modeling variance (Winkelmann, 2003). Negative binomial regression models estimate the log of the expected count
as a function of the predictor variables. The resulting coefficients are interpreted as follows: a 1-unit change in the independent
variable (e.g., having a disability) predicts a change in the difference in the logs of the expected counts of the dependent variable (i.e.,
being suspended) by the estimated coefficient, holding the other predictor variables in the model constant.
We corrected the standard errors in these models for clustering of sample students in the kindergarten schools using the Huber-
White sandwich estimator, thereby adjusting for the non-independence of data from students in the same school when the sample was
drawn in kindergarten (Cameron & Miller, 2010;Primo, Jacobsmeier, & Milyo, 2007). We used SAS PROC SURVEYREG to obtain
these estimates. Multilevel models and Huber-White sandwich estimators provide similar values for standard errors as well as fully
adjust for clustering. Difference in use is explained more by disciplinary training (e.g., economics vs. psychology) than by specific
methodological advantages. For example, McNeish, Stapleton, and Silverman (2017) reported that “similar to HLM (hierarchical
linear modeling), the CR-SE (cluster-robust standard error) estimates fully address the clustered nature of the data” (p. 118).
Arceneaux and Nickerson (2009) reported that “clustered SEs, random effects, and hierarchical models all adequately account for the
structure of the data” (p. 184). McNeish et al. (2017) further stated that cluster-adjusted standard errors made fewer assumptions
than multilevel models. Primo et al. (2007), when contrasting clustered standard errors to multilevel modeling, stated that “calcu-
lating clustered standard errors is a more straightforward and practical approach, especially when working with large datasets or
many cross-level interactions” (p. 446). Huang (2016) noted that use of cluster-adjusted standard errors based on Taylor linearization
is “well accepted, easy to implement, and is often considered the gold standard for variance estimation using complex sample data”
(p. 179). However, and as a robustness check, we re-estimated the negative binomial regression models using multi-level modeling
instead of CR-SE. The study's main results (available from the study's first author) were consistent across both analytical methods.
We standardized the continuous predictor variables to facilitate comparison of effect sizes. We used weights supplied by the NCES
to account for sample attrition by the eighth grade wave of the ECLS-K and multiple imputation to account for missing data. We used
Blimp software (Keller & Enders, 2017) when conducting the multiple imputation to account for the multilevel nature of the data
(Enders, Mistler, & Keller, 2016;Mistler & Enders, 2017). About 7% of the data were missing. We conservatively imputed 20 data sets
and then obtained parameter estimates for each. The resulting estimates were then averaged using the appropriate techniques in SAS
programming software.
We addressed the first research question by describing the detailed distribution of number of times suspended, separately for
students who did and did not have an IEP in first grade. We then estimated two regression models. The first simultaneous regression
had IEP by first grade, the interaction between IEP and race or ethnicity, and a large number of control variables as additional
predictors. The second simultaneous regression repeated this calculation, but in place of whether the student had an IEP by first grade
we used dummy variables for the student's specific disability condition. Use of simultaneous regression is recommended when, as is
the case here, the focus of the analyses is to assess the relative predicted effects of a set of possible explanatory variables on a criterion
variable (Keith, 2015). We could not include interactions between specific disability conditions and race or ethnicity in this equation
because of small sample sizes for these combinations. Instead, we continued the inclusion of interactions between IEP or not and race
or ethnicity in the model. The results from these two models answer the study's second and third research questions.
P.L. Morgan et al. Journal of School Psychology 72 (2019) 1–13
6
3. Results
3.1. Descriptive statistics
Table 1 shows the weighted descriptive statistics of the variables. In the sample of 6740 students, 16.6% had been suspended at
least once by the spring of eighth grade. Of those suspended, 10.1% had been suspended once, 3.2% were suspended twice, 1.7%
were suspended three times, 0.6% were suspended four times, and 0.9% were suspended five or more times. In the spring of first
grade, 6.8% of the sample had an IEP. Of the entire sample, 0.7% percent had SLD, 0.2% had ED, 2.1% percent had S/LI, 0.3% had ID,
0.2% had OHI, 0.5% had DD, and 0.5% had ODC.
Table 2 shows the weighted distribution of the number of times students were suspended, separately by disability status in the
spring of first grade. Overall, 20.1% and 16.3%, respectively, of students with and without disabilities in first grade had been
suspended once or more by eighth grade. This answers the study's first research question and is consistent with prior studies.
Specifically, when SWD are compared to students without disabilities and prior to controlling for other explanatory factors to make
the two groups otherwise similar, SWD descriptively had higher rates of suspension.
Table 1
Descriptive statistics of selected variables (N= 6,740), weighted.
Percentage or M (SD)
Ever suspended by 8th grade 16.6%
Suspended 1 time by 8th grade 10.1%
Suspended 2 times by 8th grade 3.2%
Suspended 3 times by 8th grade 1.7%
Suspended 4 times by 8th grade 0.6%
Suspended 5 times by 8th grade 0.9%
IEP, spring 1st grade 6.8%
White 57.3%
Black 17.3%
Hispanic 18.2%
Other race/ethnicity 7.3%
Male 51.7%
Age, fall kindergarten 68.5 (4.4)
IEP, spring 1st grade, learning disabled 0.7%
IEP, spring 1st grade, emotional disturbance 0.2%
IEP, spring 1st grade, speech or language impairment 2.1%
IEP, spring 1st grade, intellectual disability 0.3%
IEP, spring 1st grade, other health impairment 0.2%
IEP, spring 1st grade, developmental delay 0.5%
IEP, spring 1st grade, other/missing 0.5%
Enrolled in Head Start, fall kindergarten 17.4%
From non-English household, fall kindergarten 11.9%
Family SES, average −0.0 (0.8)
Externalizing problem behaviors, fall kindergarten 1.6 (0.6)
Approaches to learning, fall kindergarten 3.0 (0.7)
Reading Test score, fall kindergarten, IRT-scale score 35.1 (10.1)
Mathematics Test score, fall kindergarten, IRT-scale score 26.4 (9.1)
School's percentage of Black students, average 16.0 (20.3)
School's percentage of Hispanic students, average 13.9 (18.7)
School's percentage of students receiving free lunch, average 33.1 (24.8)
Note. IEP = Individualized Education Program; IRT = item response theory; K = kindergarten;
SES = socioeconomic status. Sample size rounded as per NCES requirements.
Table 2
Times suspended by the end of 8th grade, students with and without an IEP in first grade and total sample, weighted.
Number of times suspended Students with IEP by spring of 1st grade
(N= 390)
Students without an IEP by spring of 1st grade
(N= 6,350)
Total
(N= 6,740)
0 79.9% 83.6% 83.4%
1 13.2% 9.9% 10.1%
2 3.1% 3.2% 3.2%
3 2.1% 1.6% 1.7%
4 0.9% 0.6% 0.6%
5 0.8% 1.0% 0.9%
Note. IEP = Individualized Education Program; sample sizes rounded as per NCES requirements.
P.L. Morgan et al. Journal of School Psychology 72 (2019) 1–13
7
3.2. Negative binomial regression model results
Table 3 shows two negative binomial regression models predicting the number of times students were suspended by the spring of
eighth grade. Model 1 shows no significant coefficient of IEP on suspension. The coefficients of the interactions between IEP and race
or ethnicity were also non-significant. Further, the coefficients of the interactions between IEP and being Black or Hispanic were
negative. These results show that simultaneously controlling for an extensive set of alternative explanatory factors, we found no
support for the hypotheses that SWD were more frequently suspended than otherwise similar students without disabilities. We also
failed to find that SWD who are Black or Hispanic or of other race/ethnicity were more frequently suspended than otherwise similar
SWD who are White.
In contrast, the coefficient for students who are Black was positive and significant. This suggests that students who are Black were
suspended more frequently than otherwise similar students who are White. However, this increased risk was unrelated to having a
disability as indicated by the non-significant (and, for Black and Hispanic students, directionally inconsistent) interaction terms. The
negative binomial regression estimated the log of the number of events as an additive function of the predictors. Thus, to examine the
multiplicative effect of a variable on the expected number of events, one should exponentiate its coefficient. Exponentiating the
coefficient for Black students in Model 1 of Table 3 gives exp. (0.45) = 1.57. Thus, and on average, students who are Black received
about 1.6 times as many suspensions by the end of eighth grade as otherwise similar students who are White. (We caution, however,
that suspension is a relatively rare event. As shown in Table 1, 83.4% of the sample were never suspended and an additional 10.1%
were suspended only once.)
As for the other variables in the equation, a number of them are statistically significant. Males had a much higher rate of
suspension than females. Children who were older when they entered kindergarten had a higher rate than those who were younger.
Students from non-English-speaking households and from higher SES families were suspended less frequently. Kindergarten students
who engaged in externalizing problems more frequently were suspended more frequently during elementary and middle school.
Schools with a higher percentage of low-income students had a higher suspension rate.
Model 2 replaced the general IEP variable with the specific disability condition for which students were receiving special edu-
cation services. The IEP variable was deleted from this equation because it is redundant of having one of the specific disabilities.
(Accordingly, students within each disability category are being compared to students without disabilities.) In general, the estimates
Table 3
Weighted parameter estimates of negative binomial regression models of the number of times suspended by the end of 8th grade
(N= 6,740).
Model 1 Model 2
Intercept −2.44
⁎⁎⁎
−2.45
⁎⁎⁎
IEP in 1st grade −0.01
Black 0.45
⁎⁎
0.45
⁎⁎
Hispanic −0.06 −0.05
Other race/ethnicity −0.33 −0.34
Male 0.96
⁎⁎⁎
0.97
⁎⁎⁎
Age, fall kindergarten 0.11
⁎⁎
0.12
⁎⁎
Learning disabled 0.01
Emotional disturbance −0.14
Speech or language impairment 0.42
Intellectual disability 0.36
Other health impairment −1.46
Developmental delay −1.30
Other disability −2.31
IEP in 1st grade × Black −0.56 −0.53
IEP in 1st grade × Hispanic −0.22 −0.33
IEP in 1st grade × Other race/ethnicity 0.16 0.10
Enrolled in Head Start, fall kindergarten 0.13 0.12
From non-English household, fall kindergarten −0.65
⁎⁎⁎
−0.65
⁎⁎⁎
Family SES, average −0.29
⁎⁎⁎
−0.29
⁎⁎⁎
Externalizing problem behaviors, fall kindergarten 0.32
⁎⁎⁎
0.33
⁎⁎⁎
Approaches to learning, fall kindergarten −0.06 −0.06
Reading Test score, fall kindergarten −0.01 −0.01
Mathematics Test score, fall kindergarten −0.07 −0.07
School's percentage of Black students, average 0.06 0.05
School's percentage of Hispanic students, average 0.03 0.02
School's percentage of students receiving free lunch, average 0.21
⁎⁎⁎
0.22
⁎⁎⁎
Note. IEP =Individualized Education Program; SES = socioeconomic status. Multiple imputation and clustered standard errors
used. All models are clustered on fall kindergarten school. Twenty imputed BLIMP (Keller & Enders, 2017) datasets used.
Continuous variables standardized.
< 0.05.
⁎⁎
< 0.01.
⁎⁎⁎
< 0.001.
P.L. Morgan et al. Journal of School Psychology 72 (2019) 1–13
8
in this model are very similar to those in Model 1. As for the specific disability conditions, only ODC was statistically significant. This
had a large and negative coefficient. Thus, students with ODC were suspended less frequently during elementary and middle school
than students without disabilities, possibly because this variable includes conditions such as blindness and other physical disabilities
that may not result in disruptions of academic work in classrooms.
To summarize, the study's findings indicated that (a) even when disability status and many potential confounds were simulta-
neously controlled, students who are Black were more frequently suspended than otherwise similar students who are White; (b) the
interactions between race or ethnicity and disability status were not statistically significant after controls including for family SES,
prior behavior, and school characteristics; (c) these interactions were directionally consistent with SWD who are Black or Hispanic
being less likely to be suspended than SWD who are White; and (d) the strongest relation between specific disability condition and
frequency of suspension occurred for students with ODC, who were less frequently suspended than students without disabilities.
3.3. Robustness check
As a robustness check, we also estimated three additional regression models (i.e., Poisson regression, zero-inflated negative
binomial regression, and zero-inflated Poisson regression, results available from the first author). We found that Akaike's Information
Criteria (AIC) was lowest for the negative binomial regression of the four types of regressions that we estimated. Results from these
other models were consistent with results reported in Table 3's negative binomial regression. This suggested that the negative bi-
nomial regression results were robust to alternative regression model specifications.
4. Discussion
Establishing whether and to what extent SWD are being suspended more frequently than otherwise similar students without
disabilities is an important issue of policy, research, and practice because of suspension's adverse life-course associations with lower
academic achievement, school dropout, substance abuse, juvenile delinquency, and adult criminality (e.g., Cuellar & Markowitz,
2015;Hemphill et al., 2012;Katsiyannis et al., 2013;Noltemeyer et al., 2015). For example, more frequent suspension greatly
increases the risk for juvenile arrest (Mowen & Brent, 2016), thereby serving as a potential entry point into the metaphorical school-
to-prison pipeline. Federal legislation and regulations require U.S. states to monitor for significant disproportionality in suspension,
including for SWD who are racial or ethnic minorities (U.S. Department of Education Equity in IDEA Rule, 2016b). However, the field
has lacked strong empirical evidence as to whether schools may be inappropriately suspending SWD more frequently than otherwise
similar students without disabilities. This is because few studies have estimated the risk of being suspended more frequently, in-
cluding as examined in analyses of a nationally representative sample that simultaneously accounted for a number of alternative
explanatory factors when estimating the risk attributable specifically to having a disability. Establishing that schools are suspending
SWD more frequently than otherwise similar students without disabilities would provide suggestive evidence that U.S. schools may be
using suspension in ways that are discriminatory (e.g., NRC, 2004; OCR, 2016).
In order to avoid potential reverse causality between SWD and suspension, we coded IEP as 1 only if the student had an IEP by
first grade. Because very few suspensions occur prior to middle school (Mendez & Knoff, 2003), these students were unlikely to have
been classified as having a disability because they had previously been suspended. By measuring the relation between this definition
of IEP and the number of times suspended through the spring of eighth grade, we were able to estimate the risk of having a disability
on suspension while limiting any effect of suspension on the risk of having a disability.
Simple descriptive statistics showed that SWD have higher suspension rates than students without disabilities. However, multi-
variable regression models including controls for potential confounds fully explained this risk. Importantly, we found no significant
interactions between IEP and race or ethnicity. Significant risk factors for more frequent suspension included being Black, male,
older, raised in a English-speaking household, raised in a lower SES family, more frequently engaging in externalizing behavior
problems, and attending a school in which a higher percent of students in the school are from low-income families. For example, on
average, students who are Black receive about 1.6 times as many suspensions than otherwise similar students who are White across
elementary and middle school. However, and despite currently being an explicit target of compliance monitoring by federal legis-
lation and regulations (e.g., U.S. Department of Education Equity in IDEA Rule, 2016b), we found no evidence to suggest that SWD
who are racial or ethnic minorities are suspended more frequently than SWD who are White. Thus, and although students who are
Black are suspended more frequently, this risk is unrelated to whether they also are SWD.
4.1. Limitations
Our study has several limitations. We report risk factor estimates. Our study does not allow for causal inferences. As in prior
studies examining for disproportionality in suspension (Wright, Morgan, Coyne, Beaver, & Barnes, 2014), including for SWD (e.g.,
Achilles et al., 2007;Bowman-Perrott et al., 2013;Duran et al., 2011), our analyses relied on a parent's retrospective report of school
suspension. Parents may not always have known how often their children had been suspended. However, and as seems likely, our risk
factor estimates are conservative if the resulting measurement error was random. It is also possible that we would have observed
other results if additional measures of the dependent variables (e.g., the number of days suspended for each disciplinary infraction,
whether the suspension was in- or out-of-school) and data sources (e.g., school records, student reports, or direct observations) had
been available.
Relatedly, data collection for the ECLS-K ended at the end of eighth grade. Although suspension occurs most frequently during
P.L. Morgan et al. Journal of School Psychology 72 (2019) 1–13
9
middle school (Mendez & Knoff, 2003), we were unable to investigate whether the disparities that we observed continued to occur
during high school. We adjusted for prior behavior and achievement using measures administered during the fall of kindergarten,
which were plausibly exogenous to the occurrence of suspension throughout elementary and middle school. However, we may have
observed other results had we accounted differently for prior behavior. Alternatively, and because the ECLS-K's measure of sus-
pension surveyed parents about whether their children had been suspended by eighth grade, averaging the teacher behavioral ratings
across the elementary grades would have resulted in a more tenuous assumption of exogeneity. We did average the family's SES and
the racial and economic segregation of schools across kindergarten to eighth grade to account for the changing environmental
contexts that students experienced as they moved from the fall of kindergarten to the spring of eighth grade. The ECLS-K data were
collected until the spring of 2007. Analyses of more recently collected data are needed to replicate these findings.
4.2. Contributions and implications
Our findings have implications for federal legislation and policy as well as educational research and practice. We find suggestive
evidence that U.S. elementary and middle schools use suspension in ways that may be discriminatory, at least as indicated by the
disparities in suspension frequency not being explained by measured confounds including student-level measures of behavior, family-
level SES, and school-level racial and economic composition. For example, and consistent with some studies (e.g., Petras et al., 2011;
Skiba et al., 2011), we find that on average students who are Black are more frequently suspended than similarly situated students
who are White. Specifically, our analyses indicated that students who are Black receive about 1.6 times as many suspensions than
otherwise similar students who are White by the end of middle school. This increased risk for students who are Black for more
frequent suspension is not explained by potential confounds including student-level behavior, family SES, and school racial and
economic segregation.
Variability in both sample characteristics and statistical analysis may explain differences between our findings and those of prior
work. For example, we analyzed a nationally representative sample in which family SES was directly assessed using parental surveys
of family income, occupation, and education level. In contrast, Kinsler (2011) analyzed state-level data and controlled for SES using
school records of receipt of free or reduced-price lunch. The ECLS-K's survey of parental education, occupation, and income, which
are averaged into a single composite variable, should have better controlled for family SES (Harwell & LeBeau, 2010), which is a
strong confound of race and ethnicity (Patten & Krogstad, 2015). Because the ECLS-K data included these more proximal measures of
family SES, our analyses should have better corrected for this strong confound and so allowed more rigorous estimates of the risk of
suspension attributable to race or ethnicity.
Our findings conflict with those reported in Wright et al.'s (2014) study, in which student suspension was dichotomously mea-
sured and most control variables including disability status were contemporaneously assessed at the eighth-grade survey while prior
behavioral functioning was averaged from kindergarten, first, and third grade. In contrast, our study's individual-level predictor
variables were assessed in kindergarten and first grade while the dependent variable was instead the number of times suspended by
the end of eighth grade. We identified students as having disabilities if they had an IEP by the spring of first grade in order to limit the
possibility of reverse causality (i.e., suspension causing disability identification). We therefore did not analyze the number of times
suspended for all students who ever had an IEP. Instead, we analyzed data from first grade students who already had an IEP to
examine whether such identification increased their likelihood of being suspended. We believe that this allowed for a conservative
analysis as this subgroup of students likely included an above average share of those with more severe impairments given their earlier
disability identification. If SWD with more severe impairments were not at elevated risk for suspension, then it seems unlikely that
this would be the case for SWD with less severe impairments. We controlled for student-level behavior in kindergarten, which should
have temporally preceded suspension to further limit reverse causality. In addition, our family- and school-level variables were
averaged across all survey waves and so better accounted for changing environmental conditions students experienced from first
through eighth grade. (Averaging across waves was also the best option to represent these environmental variables because the ECLS-
K parent survey did not ask about specific dates for suspensions.) One resulting practical implication of our study is that school
psychologists, teachers, and administrators should consider early interventions for kindergarten students already engaging in ex-
ternalizing problem behaviors. These students are at increased risk of being more frequently suspended throughout the elementary
and middle school grades.
Another practical implication of our study is that teachers, school psychologists, and administrators should consider whether
students are being suspended in ways that may discriminate based on sex, race, age, or economic background. This is because, as
others have found (Petras et al., 2011;Wright et al., 2014), socio-demographic disparities in suspension frequency are not fully
explained by variability in student-level externalizing problem behavior as well as other student-level indicators of school functioning
that might reasonably be related to the frequency of suspension. Educational practices that might help address these disparities
include increasing access to race- or gender-concordant teachers and/or those experienced in working with older students, as these
teachers may be able to advise on how to appropriately manage problem behavior in culturally sensitive ways that do not result in
suspension (Lindsay & Hart, 2017). Increasing the availability of evidence-based training of culturally sensitive practices may also be
helpful. School-to-home outreach efforts to parents of children from traditionally marginalized populations may also help reduce
socio-demographic disparities in suspension frequency by helping stressed or under-resourced parents better manage their children's
externalizing problem behaviors as well as increasing the consistency of the behavior management approaches used across home and
school (Mason et al., 2016).
We find little evidence that U.S. elementary and middle schools are suspending SWD more frequently than otherwise similar
students without disabilities. Our findings do not support policies or reports (Kim et al., 2010;Losen & Gillespie, 2012;OCR, 2014)
P.L. Morgan et al. Journal of School Psychology 72 (2019) 1–13
10
that having a disability is itself associated with an increased risk of entering the school-to-prison pipeline via school suspension
(Behnken et al., 2014;Mowen & Brent, 2016) conditional on this study's other explanatory factors. This includes SWD who are racial
or ethnic minorities, who were suspended no more frequently than SWD who are White. That SWD were not suspended more
frequently than students without disabilities as they attend U.S. elementary and middle schools conflicts with some prior work
(Krezmien et al., 2006), which did not adjust for potential confounds (Losen & Gillespie, 2012) including prior behavior (GAO, 2018;
Sullivan et al., 2013). However, our findings are consistent with other studies (e.g., Theriot et al., 2010), including those few that
have similarly accounted for the strong confound of prior behavior (Kinsler, 2011;Wright et al., 2014) and have also failed to find
that SWD are more likely to be suspended than otherwise similar students without disabilities. We also fail to find empirical evidence
to support federal legislation and policies (U.S. Department of Education Equity in IDEA Rule, 2016b) requiring monitoring for
significant disproportionality in the extent to which SWD who are racial or ethnic minorities are being suspended as they attend U.S.
schools.
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... While school exclusions are issued predominantly to secondary (middle or high; ~7th to 12th grade) school students, early suspensions may represent particularly high-risk events for subsequent suspensions (Raffaele Mendez, 2003) and future poor outcomes (Bowman-Perrott et al., 2013), and thus potentially more effective targets for preventive intervention (Parsons, Godfrey, Howlett, Hayden, & Martin, 2001). Despite this, little research has focused specifically on identifying predictors of exclusions in the primary/elementary (kindergarten to 6th grade) school years (Morgan et al., 2019;Noltemeyer et al., 2015). Typically, suspensions in these years have been examined as part of data spanning kindergarten to the 12th grade, but the greater prevalence of secondary school exclusions may obscure differential predictors of exclusions during primary school. ...
... Male students, students from disadvantaged and minority backgrounds, and students with disability are disproportionately affected by exclusionary school discipline (Achilles, McLaughlin, & Croninger, 2007;Anderson & Ritter, 2017;Bal, Betters-Bubon, & Fish, 2019;Bowman-Perrott et al., 2013;Camacho & Krezmien, 2020;Cruz & Rodl, 2018;Duran, Zhou, Frew, Kwok, & Benz, 2013;Ford et al., 2018;Hemphill et al., 2010;Hemphill, Plenty, Herrenkohl, Toumbourou, & Catalano, 2014;Krezmien, Leone, & Achilles, 2006;Paget et al., 2018;Skiba et al., 2014;Sullivan, Van Norman, & Klingbeil, 2014;Welsh & Little, 2018;Wright, Morgan, Coyne, Beaver, & Barnes, 2014;Yang, Harmeyer, Chen, & Lofaso, 2018). By contrast, students with limited English proficiency show reduced risk of exclusion relative to English speaking peers (Anderson & Ritter, 2017;Bal et al., 2019;Morgan et al., 2019). Despite these replicated findings, several investigations have indicated that these associations may be reduced (Duran et al., 2013;Morgan & Wright, 2018) or even eliminated (Morgan et al., 2019) in multivariable models that account for other covariates. ...
... By contrast, students with limited English proficiency show reduced risk of exclusion relative to English speaking peers (Anderson & Ritter, 2017;Bal et al., 2019;Morgan et al., 2019). Despite these replicated findings, several investigations have indicated that these associations may be reduced (Duran et al., 2013;Morgan & Wright, 2018) or even eliminated (Morgan et al., 2019) in multivariable models that account for other covariates. For example, in Duran et al. (2013), the magnitude of the associations with school suspension or expulsion for male students, for students from low-income families, and for students with emotional-behavioural disorders reduced by between 21% and 30% when the students' social skills were entered in analyses. ...
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Out-of-school suspension is associated with adverse educational, justice, health, and welfare outcomes. Little research has focussed on suspensions from primary (elementary) school, despite early exclusions representing high-risk events for poor outcomes. This study aimed to identify early life predictors of primary school suspensions in a sample of 34,855 Australian children using linked education, health, child protection, and justice records for children and their parents. Associations between 26 sociodemographic, pregnancy/birth, child, and parent factors (measured prior to 3rd grade) and subsequent suspensions, issued during the 3rd through 6th grades (ages ~8–11 years), were examined in bivariate and multivariable logistic regressions. In the fully adjusted model, 18 factors were associated with suspension, with the largest effects for male gender, child protection services contacts, and aggressive behaviour. Identification of students at risk of early suspension using multi-sector information available at school entry may assist educators and policymakers to deliver preventative interventions.
... High rates of exclusionary discipline are thus themselves problematic, but the higher use of office referrals, suspensions, and expulsions for students of color is especially concerning. Students of color are at greater risk to receive exclusionary discipline compared to White students, with Black (i.e., African American) students being most at risk (Losen et al., 2015;Morgan et al., 2019;U.S. Government Accountability Office, 2018). ...
... Government Accountability Office, 2018). Even when controlling for factors other than race (e.g., behaviors, poverty), Black students still experience disproportionally high rates of exclusionary discipline compared to other racial groups (Bradshaw et al., 2010;Girvan, 2019;Morgan et al., 2019;Rocque, 2010). ...
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... These barriers limit the options for active and autonomous participation among students with or without visual impairment in order to achieve true educational inclusion [7,13]. Likewise, to facilitate English language learning to VISs, it is required to incorporate new methodological strategies in the teaching-learning process of the language [3,14,15]. This situation leads to new challenges and challenges to teachers, who are faced with the need to motivate and maintain the attention of students who do not have such disabilities. ...
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This document evidences an innovative methodological vision in the teaching-learning process of the English language focused on the inclusion of all its students in a heterogeneous learning environment. Learning a foreign language as a second language is a challenge that all students must overcome, but this challenge is more significant in visually impaired students. Therefore, the present research is based on a historical, descriptive process that reviews high-impact scientific articles supported by recognized databases. Later on, it warns about breaking down the stages of the process, supporting the analytical method, and then joining each stage, starting from the simple to the complex using the synthetic method, thus consummating a complete analytical-synthetic process. In this way, the present work shows a description of the methodological experience from a set of good practices for visually impaired students in the classroom environment. The proposed work systematizes the methodology applied in the educational process and categorizes the stages of the methodological process developed according to the skills and abilities required for learning by using typhlo-technical tools. On the other hand, the research determines a route map that allows and facilitates the management of the method implemented in learning the English language for students with visual impairment. Consequently, this constitutes a valid alternative for educational inclusion within an innovative environment that welcomes the use of information and communication technologies to achieve the natural inclusion and autonomous participation of students with visual impairment.
... However, when we consider whiteness and smartness as ideological property (Annamma et al., 2013), these studies fail to contend with critical issues related to the racism and ableism embedded in special education and exclusionary discipline-that they are interactional forms of oppression. Studies that rely on teacher-reported behavior ratings to "evaluate whether schools are discriminating against [students labeled with disabilities] when using suspension" (Morgan et al., 2019, p. 3) fail to understand the interlocking narratives of race, dis/ ability, and stereotypes that lead to suspension and notions of "at risk" that can be better interrogated through qualitative works. These studies have relied on problematic assumptions, including that students identified in first grade "should have had more severe impairments due to their earlier identification and so displayed greater academic or behavioral difficulties than students identified as having disabilities in the later grades" (Morgan, p. 5). ...
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... Many factors contribute to the gap in reading achievement between AA students and students of other racial groups. AA students are more likely to be suspended or expelled than their White peers, even after controlling for several student-level factors (Gopalan & Nelson, 2019; but see Morgan et al., 2019), thereby resulting in decreased instructional time. Furthermore, some researchers suggest that restricted access to health care services decreases the likelihood that AA students with language and/or learning disorders will receive the early intervention services they need (P. ...
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Research has suggested that students from underserved and underrepresented backgrounds (e.g., students of color and those with disabilities) have received higher rates of exclusionary discipline (e.g., suspensions and expulsions) than their peers who are White and without disability. Various interventions have been implemented to address this issue; however, disproportional disciplinary practices remain an area of concern for school leaders and researchers. The current article posits an alternative approach to this issue through reframing how we think of education and exclusionary discipline. Addressing behavior through the lens of behavioral functioning allows for teachers and administrators to be able to better pinpoint “why” a student is engaging in a behavior that may lead to disciplinary infractions. This approach can help with disproportional disciplinary practices as determining behavioral functioning helps to drive effective intervention, which, when implemented with fidelity, should reduce the need to remove the student from class. Supplemental data for this article is available online at https://doi.org/10.1080/1045988X.2021.1937023 .
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Federal legislation and policy increasingly seek to address minority overrepresentation in special education due to concerns that U.S. schools are misidentifying children as disabled based on their race or ethnicity. Yet whether and to what extent this is occurring is currently in dispute. We estimated racial disparities in disability identification using very large (e.g., Ns = 183,570, 165,540, and 48,560) student-level, nationally representative data sets and multivariate logistic regression including school fixed effects models along with tabulations of percentage with a disability among racial or ethnic groups across academic achievement deciles. Among children who were otherwise similar in their academic achievement, poverty exposure, gender, and English language learner status, racial or ethnic minority children were consistently less likely than White children to be identified as having disabilities. Minority children’s disability underidentification was evident (a) in elementary, middle, and high school; (b) across racially diverse groups and specific disability conditions; and (c) throughout the achievement distribution. Contrary to federal regulatory and policy efforts, minority children have been less likely than otherwise similarly achieving White children to receive special education services in the United States since at least 2003.
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There is much discussion in the United States about exclusionary discipline (suspensions and expulsions) in schools. According to a 2014 report from the U.S. Department of Education's Office for Civil Rights, Black students represent 15% of students, but 44% of students suspended more than once and 36% of expelled students. This analysis uses seven years of individual infraction-level data from public schools in Arkansas. We find that marginalized students are more likely to receive exclusionary discipline, even after controlling for the nature and number of disciplinary referrals, but that most of the differences occur across rather than within schools. Across the state, black students are about 2.4 times as likely to receive exclusionary discipline (conditional on reported infractions and other student characteristics) whereas within school, this same conditional disparity is not statistically significant. Within schools, the disproportionalities in exclusionary discipline are driven primarily by non-race factors such as free-and reduced-price lunch (FRL) eligibility and special education status. We find, not surprisingly, that schools with larger proportions of non-White students tend to give out longer punishments, regardless of school income levels, measured by FRL rates. Combined, these results appear to indicate multiple tiers of disadvantage: race drives most of the disparities across schools, whereas within schools, FRL or special education status may matter more.
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Objectives Drawing on the racial threat and intergroup contact literatures, we explore whether (1) a school’s racial or ethnic context increases school suspensions for Black, Hispanic, and White students; (2) intergroup contact among school board members reduces school suspensions for Black, Hispanic, and White students; and (3) a school’s racial or ethnic context effects on school suspensions are conditioned by intergroup contact among school board members. Method Count-dependent multilevel modeling techniques on school- and district-level measures from a representative sample of Florida middle and high schools. Results Larger racial and ethnic student populations within schools increase the likelihood of suspensions for Black and Hispanic students while decreasing suspensions for White students. Further, higher levels of intergroup contact between Black, White, and Hispanic school board members are associated with a lower likelihood of suspensions for all students. Finally, intergroup contact between Black, White, and Hispanic school board members moderates the effects of school racial and ethnic context on school suspensions. Conclusions Important factors are associated with school punishment for Black, Hispanic, and White students. Integrated spaces play an important role in decreasing both punishment disparities and punishment severity.
Book
Multiple Regression and Beyond offers a conceptually-oriented introduction to multiple regression (MR) analysis and structural equation modeling (SEM), along with analyses that flow naturally from those methods. By focusing on the concepts and purposes of MR and related methods, rather than the derivation and calculation of formulae, this book introduces material to students more clearly, and in a less threatening way. In addition to illuminating content necessary for coursework, the accessibility of this approach means students are more likely to be able to conduct research using MR or SEM--and more likely to use the methods wisely. This book: • Covers both MR and SEM, while explaining their relevance to one another • Includes path analysis, confirmatory factor analysis, and latent growth modeling • Makes extensive use of real-world research examples in the chapters and in the end-of-chapter exercises • Extensive use of figures and tables providing examples and illustrating key concepts and techniques New to this edition: • New chapter on mediation, moderation, and common cause • New chapter on the analysis of interactions with latent variables and multilevel SEM • Expanded coverage of advanced SEM techniques in chapters 18 through 22 • International case studies and examples • Updated instructor and student online resources.
Article
There is growing concern that suspensions trigger a ‘‘downward spiral,’’ redirecting children’s trajectories away from school success and toward police contact. The current study tests this possibility, analyzing whether and in what ways childhood suspensions increase children’s risk for juvenile arrests. Combining 15 years of data from the Fragile Families and Child Wellbeing Study with contextual information on neighborhoods and schools, I find that suspensions disproportionately affect children already enduring considerable adversity. Even so, suspensions appear to redirect children’s trajectories, more than doubling their risk of arrest. Although suspended children experienced greater escalations in behavioral problems than their peers, post-suspension behavioral changes explained relatively little of the association between early suspension and later arrest. Instead, the most consequential way suspended children diverged from their peers was their heightened risk for repeated school sanction. Suspended children’s risk for repeated school removal explained 52 percent of the association between childhood suspension and juvenile arrest.
Article
Multiple imputation methods can generally be divided into two broad frameworks: joint model (JM) imputation and fully conditional specification (FCS) imputation. JM draws missing values simultaneously for all incomplete variables using a multivariate distribution, whereas FCS imputes variables one at a time from a series of univariate conditional distributions. In single-level multivariate normal data, these two approaches have been shown to be equivalent, but less is known about their similarities and differences with multilevel data. This study examined four multilevel multiple imputation approaches: JM approaches proposed by Schafer and Yucel and Asparouhov and Muthén and FCS methods described by van Buuren and Carpenter and Kenward. Analytic work and computer simulations showed that Asparouhov and Muthén and Carpenter and Kenward methods are most flexible, as they produce imputations that preserve distinct within- and between-cluster covariance structures. As such, these approaches are applicable to random intercept models that posit level-specific relations among variables (e.g., contextual effects analyses, multilevel structural equation models). In contrast, methods from Schafer and Yucel and van Buuren are more restrictive and impose implicit equality constraints on functions of the within- and between-cluster covariance matrices. The analytic work and simulations underscore the conclusion that researchers should not expect to obtain the same results from alternative imputation routines. Rather, it is important to choose an imputation method that partitions variation in a manner that is consistent with the analysis model of interest. A real data analysis example illustrates the various approaches.
Article
The Secretary amends the regulations under Part B of the Individuals with Disabilities Education Act (IDEA) governing the Assistance to States for the Education of Children with Disabilities program and the Preschool Grants for Children with Disabilities program. With the goal of promoting equity under IDEA, the regulations will establish a standard methodology States must use to determine whether significant disproportionality based on race and ethnicity is occurring in the State and in its local educational agencies (LEAs); clarify that States must address significant disproportionality in the incidence, duration, and type of disciplinary actions, including suspensions and expulsions, using the same statutory remedies required to address significant disproportionality in the identification and placement of children with disabilities; clarify requirements for the review and revision of policies, practices, and procedures when significant disproportionality is found; and require that LEAs identify and address the factors contributing to significant disproportionality as part of comprehensive coordinated early intervening services (comprehensive CEIS) and allow these services for children from age 3 through grade 12, with and without disabilities.
Article
Objectives To examine how school discipline may serve as a negative turning point for youth and contribute to increased odds of arrest over time and to assess whether suspensions received across multiple years may present a “cumulative” increase in odds of arrest. Methods Using four waves of data from the National Longitudinal Survey of Youth, we use a longitudinal hierarchical generalized linear model (HGLM) to explore how school suspensions contribute to odds of arrest across time while controlling for a number of theoretically important dimensions such as race, age, delinquency, and gender among others. Results Results show that youth who are suspended are at an increased risk of experiencing an arrest across time relative to youth who are not suspended and that this effect increases across time. Further, with each subsequent year the youth is suspended, there is a significant increase in odds of arrest. Conclusion Supporting prior work, we find that youth who receive a suspension are at an increased odds of contact with the criminal justice system, and increases in the number of suspensions received contribute to significant increases in odds of arrest. Findings demonstrate that suspensions present a form of cumulative effect over time.