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Interaction Effects in Multiple Regression
... 4 In Step 2, the interaction term between contextual information and NFC scores was entered. Participants' NFC scores were mean-centered for the regression analysis to avoid multicollinearity and to ease the interpretation of the interaction regression coefficient (Jaccard & Turrisi, 2003). Regression statistics are reported in Table 2. . ...
... In Step 2, the interaction term between contextual information and NFC scores was entered. Participants' NFC scores were mean-centered for Step 2 of the regression analysis to avoid multicollinearity and to ease the interpretation of the interaction regression coefficient (Jaccard & Turrisi, 2003). Regression statistics are reported in Table 3. ...
Previous research has shown that mock and actual jurors give little weight to actuarial sexual offending recidivism risk estimates when making decisions regarding civil commitment for so-called sexually violent predators (SVPs). We hypothesized that non-risk related factors, such as irrelevant contextual information and jurors’ information-processing style, would influence mock jurors’ perceptions of sexual recidivism risk. This preregistered experimental study examined the effects of mock jurors’ (N = 427) need for cognition (NFC), irrelevant contextual information in the form of the offender’s social attractiveness, and an actuarial risk estimate on mock jurors’ estimates of sexual recidivism risk related to a simulated SVP case vignette. Mock jurors exposed to negative risk-irrelevant characteristics of the offender estimated sexual recidivism risk as higher than mock jurors exposed to positive information about the offender. However, this effect was no longer significant after mock jurors had reviewed Static-99R actuarial risk estimate information. We found no support for the hypothesis that the level of NFC moderates the relationship between risk-irrelevant contextual information and risk estimates. Future research could explore additional individual characteristics or attitudes among mock jurors that may influence perceptions of sexual recidivism risk and insensitivity to actuarial risk estimates.
... To reduce the potential multicollinearity arising from multiplicative interaction terms (Aiken and West 1991) and to yield coefficient estimates within the observable range of the independent variables (Friedrich 1982; Jaccard, Turrisi, and Wan1990), we mean centered all the explanatory variables and interactions created as the product of the meancentered components (see Brown, Dev, and Lee 2000;Jaccard, Turrisi, and Wan 1990;Rokkan, Heide, and Wathne 2003). ...
... This interpretation is distinct from the "constant effect of one variable over all values of another variable" (Aiken and West 1991, p. 38) interpretation, as is the case with uncentered (raw) data. However, both approaches are consistent in that estimates of the latter may be recovered as a special case of the mean-centered approach, if required (Freidrich 1982). 2 Table 1 shows evidence of considerable multicolinearity between the interaction variables and their components; such multicolinearity is known to inflate the standard errors of the parameter estimates, though the estimates themselves remain unbiased (Jaccard, Turrisi, and Wan 1990). The statistical significance of the higher-order interactions in the presence of the lower-order terms indicates that the imprecision due to multicolinearity does not pose a threat to validity (Buvik and John 2000). ...
Gray market activity has become increasingly prevalent. The prevailing wisdom in marketing is to use more severe enforcement to deter gray marketing. However, the certainty and speed of enforcement may also have a bearing on the incidence of violations. This article examines whether and how enforcement deters gray marketing. The results from a field survey of manufacturers and an experimental design suggest that, by itself, enforcement severity has no impact. Deterrence results only when the multiple facets of enforcement are used in combination.
... Rather, previous research has not been able to effectively examine the complex interactions between demographic factors due to the difficulty in doing so with regression analysis. When including interaction terms in regression models, it is necessary to also include all of the lower order terms (Jaccard and Turrisi 2003). For example, suppose a researcher using regression analysis wanted to examine the combined effects of gender (G), education (E), age (A), political orientation (P), and income level (I). ...
... There is also an increased likelihood of issues due to multicollinearity, further dissuading use of such complex interaction terms. As such, most researchers using regression avoid going beyond two-way interactions, which have relatively straightforward interpretations, and only occasionally use three-way interactions, which are difficult to interpret (Jaccard and Turrisi 2003). I propose that using QCA to explore causal complexity associated with environmental concern is one way to overcome this limitation of previous research. ...
Studying how people understand and develop concern for environmental problems is a key area of research within environmental sociology. Previous research shows that numerous social factors have measurable effects on environmental concern. However, results tend to be somewhat inconsistent across studies on this topic. One possible explanation for this is because these social factors are typically examined as independent from one another. However, these factors are interrelated in complex ways, as shown by research on the moderating effects of race and political ideology on education. Using qualitative comparative analysis (QCA), this study examines the complex ways in which previously identified social factors interact with one another to affect environmental concern. The findings suggest that aside from political ideology, all of the other factors should be understood in combination with others. The findings also suggest equifinality and asymmetry as there are multiple distinct pathways to environmental concern.
... La primera de ellas es su efecto directo, como el que expresa una variable independiente X sobre el resultado Y, mientras que la segunda manera es considerar su condición de mediadora (Z) del efecto de otra variable (X) sobre el número de fta's (Jaccard y Turrisi, 2003). Ello se expresaría en el impacto que tiene, por ejemplo, la democracia sobre el número esperado de acuerdos, dependiendo de la transformación que experimenta el Estado como actor económico. ...
... En el caso de la utilización de interacciones, su propósito principal responde al testeo de las variables y a una mayor riqueza interpretativa de los resultados, mediante la introducción de dependencia de los efectos de una variable por una tercera. En función de este objetivo, se supedita a la problemática de la multicolinealidad, que además es problema de mayor relevancia en un modelo lineal, que no es el que se implementa en este artículo (Harrel, 2001;Jaccard y Turrisi, 2003). ...
Entre 1970 y 2015 América Latina experimentó un sostenido incremento en los números de sus acuerdos comerciales, período en el también se experimentaron importantes transformaciones en sus sistemas económicos orientados hacia las reformas de mercados. En el presente documento, se argumenta que la puesta en vigor de este tipo de instrumentos es explicada en mayor medida por la implementación de reformas de mercado, especialmente como mediadoras del efecto que tienen características específicas de la región, como su dependencia de los recursos naturales o su declive industrial, y de otras variables señaladas en la literatura especializada, como mayores niveles de democratización.
... To investigate whether need for achievement moderated the effect of length of instructions on the outcome variables we performed four separate hierarchical regression analyses with identification, irritation, accuracy and productivity as separate outcomes, while controlling for background variables Cohen & Cohen, 1983;Jaccard & Turrisi, 2003). In the first step, we entered simultaneously the standardized scores of the control variables, need for achievement, length, complexity and the interaction term of length and complexity as predictors, while in a second step, the interaction term between length and need for achievement was added as a predictor (see Table 3). ...
... Next, we merged the results of the LEGO and Excel experiments in a single dataset, and transformed actual productivity scores into relative productivity scores (a percentage score) 2 . Finally, a hierarchical regression analysis Cohen & Cohen, 1983;Jaccard & Turrisi, 2003) and the procedures proposed by Dawson (2014) and Dawson and Richter (2006), showed a significant interaction effect of increase in task difficulty and instruction length on productivity (β = .29, p < .001, ...
... Existing computational methods evaluate genome-transcriptome or microbiome-transcriptome associations in isolation, without explicitly modeling the additive effects or GMIs [8][9][10][11]. In multiple regression, interaction terms, which capture the multiplicative effect between two variables, enable the modeling of the dependency where the effect of one variable on the outcome may depend on the value of another variable [12]. The multiplicative interaction terms have been used to represent the interaction between genotype and environment in modeling phenotypes [5,13]. ...
Gene expression is a molecular phenotype shaped by the interplay between genotype and environment. The microbiome represents a critical environmental exposure for the host. However, the genotype-microbiome interactions (GMIs) shaping the host transcriptome remain largely unexplored. Here, we integrated conjunctival multiomics data from 120 pairs of twins to investigate GMIs. We identified 272,972 expression quantitative trait loci associated with 5946 genes and 241,073 genotype-controlled correlations between gene expression and microbial abundance. We developed a modeling approach, MicroGenix, that screens for GMIs from host genome, transcriptome, and microbiome data and identifies GMIs associated with the disease through gene-based association tests. We applied MicroGenix to the conjunctival data set and found that incorporating GMIs into gene expression prediction models significantly increased prediction accuracy. The genes with increased accuracy were overrepresented by those encoding cell adhesion molecules. We further used MicroGenix to predict the transcriptome from conjunctival metagenomes iMetaOmics. 2024;e37. wileyonlinelibrary.com/journal/imo2 |
... Moderation was explored via interaction terms between anxiety and flexible restraint and GAD and flexible restraint. Anxiety and flexible restraint were mean-centred prior to creating interaction terms to aid with interpretability (Haldar, Jackard, Turrisi, & Wan, 1990;Montoya, 2019). The simple slopes procedure was used to present the moderation effect graphically, to show how the anxiety-snacking association differed between three categories of flexible restraint (low: mean -1SD, medium: mean, high: mean +1SD) (Aiken et al., 1991). ...
Anxiety and snacking increased during the initial coronavirus disease 2019 (COVID-19) lockdowns, but it remains unknown whether this change in snacking persisted and if it related to anxiety levels. We used prospective data to examine changes in snacking frequency from t1 (eased restrictions in England in May-June 2020) to t2 (national lockdown in December 2020-March 2021), the association of anxiety (assessed by the Generalised Anxiety Disorder-7 questionnaire at t1) with the snacking change, and the mediating and moderating effects of disinhibition and flexible restraint (assessed by the Three Factor Eating Questionnaire in 2016-17). Analyses including 2128 adults (mean age 28.4y) residing in England from the Avon Longitudinal Study of Parents and Children showed that snacking frequency increased (mean change 1.23 (95% CI 0.81,1.65) snacks/wk). Linear regressions of snacking adjusted for sociodemographic covariates showed that having clinical levels of generalised anxiety at t1, versus not, was associated with 1.22 (95% CI 0.07,2.37) more snacks/wk at t2, disinhibition partially mediated the association between probable Generalised Anxiety Disorder (GAD) and snacking (βindirect = 0.15, 95% CI 0.01,0.32), but flexible restraint did not moderate the association (β = 0.05, 95% CI -0.57,0.66). Our longitudinal findings highlight a detrimental anxiety-snacking association partly operating via disinhibition, suggesting future research could target mitigating anxiety and disinhibited eating behaviours to benefit diet-related outcomes following the pandemic.
... To test H 1 , H 4 , and H 5 , we considered the inverted U-shaped moderating effects of three moderators-influencer activity, follower-brand fit, and post positivity-on engagement elasticity. Specifically, we added interactions of the quadratic forms of the proposed moderators with ln(IMS ij ) (i.e., Influencer Activity 2 ij × ln(IMS ij ), Follower Brand Fit 2 ij × ln(IMS ij ), and Post Positivity 2 ij × ln(IMS ij )) and the simple quadratic forms of the three moderators (i.e., Influencer Activity 2 ij , Follower Brand Fit 2 ij , and Post Positivity 2 ij ) to the engagement model in Equation 2 to test for curvilinear moderating effects (Jaccard and Turrisi 2003;Lind and Mehlum 2010;Wielgos, Homburg, and Kuehnl 2021). We introduced the interactions of each quadratic moderator with ln(IMS ij ) stepwise (Models 3a-3c), then collectively (Model 3). ...
Influencer marketing initiatives require firms to select and incentivize online influencers to engage their followers on social media in an attempt to promote the firms’ offerings. However, limited research considers the costs of influencer marketing when evaluating these campaigns’ effectiveness, particularly from an engagement elasticity perspective. Moreover, it is unclear whether and how marketers might enhance influencer marketing effectiveness by strategically selecting influencers, targeting their followers, or managing content. This study draws on a communication model to examine how factors related to the sender of a message (influencer), the receiver of the message (influencer’s followers), and the message itself (influencer’s posts) determine influencer marketing effectiveness. The findings show that influencer originality, follower size, and sponsor salience enhance effectiveness; posts that announce new product launches diminish it. Several tensions arise when firms select influencers and manage content: Influencer activity, follower–brand fit, and post positivity all exert inverted U-shaped moderating effects on influencer marketing effectiveness, suggesting that firms that adopt a balanced approach along these dimensions can achieve greater effectiveness. These novel insights offer important implications for marketers designing influencer marketing campaigns.
... We recommend effect or sum-to-zero coding for the MCM because the goal is to establish a common reference from which each origin-destination combination may deviate (Aiken, West, and Reno 1991;Jaccard and Turrisi 2003). That is, the effect coding is preferred for the MCM because the parameters all have the same referent group-the next lower level in the hierarchy of main effects and interactions. ...
Intergenerational social mobility has immense implications for individuals’ well-being, attitudes, and behaviors. However, previous methods may be unreliable for estimating heterogeneous mobility effects, especially in the presence of moderate- or large-scale intergenerational mobility. I propose an improved method, called the “mobility contrast model” (MCM). Using simulation evidence, I demonstrate that the MCM is more flexible and reliable for estimating and testing heterogeneous mobility effects, and the results are robust to the scale of intergenerational mobility. I revisit the debate about the effect of mobility on fertility and analyze data from the 1962 Occupational Changes in a Generation Study (OCG-1) and more recent data from the 1974 through 2018 General Social Survey (GSS) using previous models and the MCM. The MCM suggests a small association between fertility and occupational mobility in the GSS data but substantial and heterogeneous educational mobility effects on fertility in the OCG-1 and the GSS. Such effects are difficult to pinpoint using previous methods because mobility effects of different magnitudes and opposite directions among mobility groups may cancel each other out. The new method can be extended to investigate the effect of intergenerational mobility across multiple generations and other research areas, including immigrant assimilation and heterogamy.
... 7 An interaction term between income and age was therefore added to the model. In order to assist interpretation and avoid possible problems of multicollinearity, the age and income variables were 'centred' by subtracting the mean of each variable (in this case the mean of the midpoint values) from each of its values (mean income = $ 60148; mean age = 51 years) (following procedures suggested by Aiken et al 1991;Jaccard et al 1990). 8 Multiplying the two centered variables then created the interaction term (income centered * age centred). ...
Published in: Voluntary Action: The Journal of the Institute for Volunteering Research, 4(3), 2002, pp.78-95.
... In the model in Table 5 in the main text, repeated here as Table 6, we elect to mean center continuous variables to counteract collinearity that becomes evident when including the interaction between verb baseline average and lexical typicality. Although some debate exists regarding the practice of transforming variables (Belsley, 1991;Echambadi & Hess, 2007), centering variables is common practice to remove nonessential ill conditioning, that is, relationships that inevitably exist between main and product terms (Aiken et al., 1991;Jaccard & Turrisi, 2003;Jaeger, 2008). We note that if verb baseline mean is not centered, collinearity is high (VIF=15.79) in this model. ...
... In the model in Table 5 in the main text, repeated here as Table 6, we elect to mean center continuous variables to counteract collinearity that becomes evident when including the interaction between verb baseline average and lexical typicality. Although some debate exists regarding the practice of transforming variables (Belsley, 1991;Echambadi & Hess, 2007), centering variables is common practice to remove nonessential ill conditioning, that is, relationships that inevitably exist between main and product terms (Aiken et al., 1991;Jaccard & Turrisi, 2003;Jaeger, 2008). We note that if verb baseline mean is not centered, collinearity is high (VIF=15.79) in this model. ...
... La comparación del coeficiente de determinación lineal obtenido en los tres modelos permite concluir que el Modelo Teórico presenta un ajuste significativamente mejor que el resto. Para analizar el efecto de las variables independientes sobre la participación activa del distribuidor en el mercado paralelo, y puesto que el modelo incluye efectos no lineales e interacción, se sigue el procedimiento propuesto por Aiken y West (1991) y Jaccard et al. (1990). Así, el efecto de RES sobre PAC, en presencia de ENF, se describe con la siguiente función (2): (2) En el estudio de la extensión total del rango de una variable se consideran valores bajos a aquellos con un valor de -1 desviación típica y, como valores altos, +1 desviación típica (Aiken y West, 1991). ...
El propósito del artículo es el análisis de la estrategia dentro de la cadena de suministro de artículos de gran consumo. El diseño del canal de distribución es una situación crítica donde se confronta la estrategia con el comportamiento de los agentes. Se observa que la alternativa del distribuidor en caso de disconformidad con el surtido asignado es el recurso al mercado paralelo. El análisis conduce al estudio del efecto de la disciplina del fabricante sobre el canal para hacer cumplir la estrategia de distribución oficial. Las conclusiones son expuestas a partir de resultados obtenidos en un análisis empírico.
... In the terminology of Jaccard and Turrisi (2003), the economic evaluation constitutes the focal variable in the model. Political knowledge acts as a first-order moderator, as the effect of the economy is expected to change depending on the level of political knowledge the voter holds. ...
This study aims to provide a comprehensive view of the role of political information in retrospective voting by simultaneously investigating the effects of levels of information on the individual level and the availability of information on the contextual level. It is argued that the sophistication-gap in retrospective voting is confined to those contexts in which it is hard for voters to assign responsibility for the country’s state of affairs to the correct political party/-ies. Contrary to this expectation, analyses using the CSES data show that there is a larger difference in retrospective voting between voters with different levels of political information in high-clarity contexts, while voters do not seem to hold incumbent parties to account at the polls in low-clarity contexts – irrespective of their level of political knowledge. However, additional analyses show variation in this result depending on the data and measures used.
... Finally, most economic activities have a direct or indirect negative environmental impact (Grossman and Krueger 1995Suri and Chapman 1998Shafik 1994. Thus, the size of a country's economy could also impact the incentive-structure of states to get active in Capabilities and incentives could also interact (Coulton andChow 1993, Jaccard andTurrisi 2003). In general, the positive effect of capabilities on the likelihood that states make use of ...
From the late 1960s and early 1970s onwards, environmental politics were not only put increasingly on domestic agendas, but also dealt with in international regimes and organizations (IOs). The rise of environmental IOs has led to the expectation of a greening of international politics and a corresponding contribution to improved environmental standards around the globe. This paper opens the black box of environmental negotiations in IOs and examines how active the various IO member states participate in the process of deciding upon international environmental rules and norms. This reveals two interesting empirical puzzles that the paper examines in a theory-guided methodological sound manner. First, many states joined environmental IOs and contribute to them through membership fees, but nevertheless often fail to make use of their formal right to voice positions in international environmental negotiations. Second, some states are considerably more outspoken than others, although articulating one’s position is important for the chances to influence international environmental policies. The paper argues that the former is due to lack of capabilities, while the latter is due to differences in the saliency of environmental topics across states.
... for country affect, the coefficient is À.37, p < .05). We further calculated the effect of both country image and country affect on WTB on three different levels of ambivalence (Jaccard and Turrisi 2003), finding that the mitigating effect increases from low to high levels (as indicated by decreasing standardized path coefficients). In addition, we examined the direct effect of country image (.57, p < .001) ...
Understanding how consumers use a product’s country-of-origin (COO) cue is fundamental to explaining their behavior in a globalized marketplace. While the study of COO is one of the most popular topics in international marketing, the ambiguity regarding its conceptualization, composite nature, operationalization, and measurement deserves further scrutiny. The authors propose an integrative framework that unites two separate areas of research on the COO cue: performance-related COO images and performance-unrelated country emotions. The authors reconcile diverse existing perspectives from both areas into the overarching country-induced predispositions model. Conceptualizations and measurement approaches for the model’s five components are developed and empirically validated across three countries and with five COOs. The model offers researchers and managers with an interest in the COO cue a flexible and operational roadmap, with scales both for in-depth analyses and parsimonious additional testing.
... Hence, a Regression Model (such as expressed by equation 7) cannot accurately estimate the impact of the predictor variables "area of wall" and "U-value of wall" on heat gain/loss inside a building (and consequently, the "Cooling Load" (CL)). CL= β 0 + β 1 *A wall + β 2 *U wall (7) The strategy suggested to overcome this problem is, to add a product term to the main effect model (Jaccard and Turrisi, 2003;Cortina, 1993). This strategy was also used by Hygh et al. (2012) to refine their model. ...
Building Performance Simulation (used to assess and validate claims about energy requirement of buildings), is often carried out during later design stages, when it is practically difficult to incorporate design changes. In reality, many design decisions affecting Energy requirement of buildings are taken at an early stage, when adequate information to support such decisions is not available or viable due to lack of tools. This paper presents the suitability of data driven techniques, particularly Artificial Intelligence and Machine learning, for early-design-decision support tools through a systematic review of literature. It highlights their potential due to robust prediction capabilities and forms groundwork for further research to develop an early-design-decision support tool.
... It refers to a general situation when it is not adequate to build a model with the original explanatory variables alone in a simple additive way -referred to as the main effects. At the same time, it could be more effective to build a model incorporating constructed variables as the products between pairs of variables -referred to as the interactions between the variables; see, for example, the monograph of Jaccard and Turrisi (2003) for an overview. Since the interactions are constructed from the predictor variables, it is clear that conceptually they can be further expanded in a hierarchical manner. ...
In statistical methods, interactions are the contributions from the products of the predictor variables to the response variable. In high-dimensional problems, detecting interactions is challenging due to the combinatorial complexity in conjunction with limited data information. We consider detecting interactions by exploring their connections with the principal Hessian matrix. To handle the challenging high dimensionality, a one-step synthetic approach is proposed to estimate the principal Hessian matrix by a penalized M-estimator. An alternating direction method of multipliers (ADMM) is proposed to efficiently solve the encountered regularized optimizations. Based on the sparse estimator, we propose a new method to detect the interactions by identifying the nonzero components. Our method directly targets at the interactions, and it requires no structural assumption on the hierarchy between the interactions effects and those from the original predictor variables. We show that our estimator is theoretically valid, computationally efficient, and practically useful for detecting the interactions in a broad spectrum of scenarios.
... Second, the maximum condition index was 15.63, which is well below 30, the level that signals detrimental multicollinearity (Mason and Perreault 1991). Thus, multicollinearity does not appear to present an issue in this study (Jaccard, Turrisi, and Wan 1990). ...
Unlike their counterparts in developed markets, emerging-market firms are characterized by limited resources, including international experience and access to relevant information, which are essential for developing suitable international marketing strategy (IMS). Under such circumstances, strategies are expected to produce suboptimal results, especially when targeting competitive markets in advanced economies. Prior IMS research has largely focused on developed markets. In contrast, the authors examine IMS of exporters in Thailand, an emerging market. Despite major differences in environments and processes in emerging markets, they establish that Thai exporters that match their IMS to local market conditions realize superior performance, as predicated by strategy coalignment. The authors validate these results and discuss emerging-market firms’ capacity to adapt their strategies and succeed in highly competitive advanced economies, despite relative inexperience, volatility, and information asymmetry at home. Exporting remains of critical importance to the economies of emerging markets, and the findings provide greater optimism for their firms’ ability to address host-market conditions in their marketing strategies, as well as pointing to the competitive threat posed by these emerging-market neophytes.
... The four interactions involve supplier punitive actions and the four power asymmetry variables. The predictor variables involved in the interactions were mean-centered, a procedure commonly recommended to reduce multicollinearity and provide unbiased parameter estimates (Aiken and West 1991;Jaccard, Turrisi, and Wan 1990). To check if this was successful, we employed two widely used measures of multicollinearity (Judge et al. 1988). ...
Using data from automobile dealers in the Netherlands, the authors find that dealers’ punitive actions toward their key suppliers are affected by their perceptions of their own and their supplier's interdependence and punitive capabilities, as well as by the supplier's punitive actions. Punitive actions are affected by interdependence, but a more complete picture is achieved by also examining punitive capability. The authors test hypotheses based on bilateral deterrence, conflict spiral, and relative power theories, but none of these comprehensively explains the effects of both total power and power asymmetry. Dealer punitive actions are inhibited as total interdependence increases, but are promoted as total punitive capability increases. Using spline regression, the authors find that interdependence asymmetry has no direct effect on punitive actions, whereas punitive capability asymmetry does. As dealers’ punitive capability advantage as compared with their suppliers’ increases, dealers make greater use of punitive actions, whereas they use fewer punitive actions as their punitive capability deficit increases. The authors also find that dealers with a relative advantage in dependence or punitive capability are more likely to reciprocate their supplier's punitive actions.
... The independent variables were mean centered before forming the multiplicative term to avoid multicollinearity problems (Cronbach 1987). A statisti- cally significant two-way interaction suggests further analysis to understand the nature of the interaction (Jac- card, Turrisi, and Wan 1990). This analysis was done by looking at the simple main effect of one variable (e.g., retailer's long-term orientation) at different levels of the moderator variable (level of conflict). ...
In recent years, retailers have placed greater emphasis on developing long-term relationships to obtain sustainable benefits on issues such as product quality, price, and markdown allowances. The author examines the impact of situational factors such as the time orientation of a relationship and the importance of the issues to be resolved on the use of various negotiation strategies (problem solving, compromise, and aggressive) in channel relationships. He also investigates the impact of different strategies on channel member outcomes and satisfaction. The data used to test the model were obtained in a mail survey of 124 retail buyers in six regional department store chains. The study results indicate that when retailers are long-term oriented, problem-solving and passive aggressive strategies are used for resolving conflicts on major issues. The use of problem-solving strategy to resolve major conflicts resulted in higher outcomes and greater satisfaction than either compromise or aggressive strategies. The findings also provide insights on the use of various negotiation strategies by retailers to resolve conflicts on important and relatively unimportant issues.
... Although there are many proposed approaches to modeling nonlinear terms (for a summary, see Jaccard, Turrisi, and IJaccard and Wan's (1995) results suggest that ML statistics for model fit and significance may be appropriate for interactions and quadratics specified with four or fewer indicants. 1 e x2x2 Wan 1990), there are three general categories of approaches to estimating interaction and quadratic effects involving latent variables: product term regression analysis, subgroup analysis, and indicant product analysis. ...
The author proposes an alternative estimation technique for quadratic and interaction latent variables in structural equation models using LISREL, EQS, and CALIS. The technique specifies these variables with single indicants. The loading and error terms for the single indicants can be specified as constants in the structural model. The author's technique is shown to perform adequately using synthetic data sets.
... Moreover (cf. Jaccard, Turrisi, and Wan 1990), in the presence of a significant interaction effect, a main effect indicates the effect of a variable on the dependent variable when the other component of the interaction is at its mean level (which is zero after our standardization of the predictor variables). Because the reported coefficients (B's) reflect standardized parameter estimates, they are directly indicative of effect size, thereby enabling comparison across predictors. ...
The authors address two key issues that have received inadequate attention in the choice behavior literature on variety seeking. First, they explicitly separate true variety-seeking behavior (i.e., intrinsically motivated) from derived varied behavior (i.e., extrinsically motivated). Second, they hypothesize variety-seeking behavior to be a function of the individual difference characteristic of need for variety and product category–level characteristics that interact to determine the situations in which variety seeking is more likely to occur relative to repeat purchasing and derived varied behavior. The authors test their hypotheses in a field study of Dutch consumers, which assesses both the intensity of brand switching and the underlying motives for their switching behavior. Results support the importance of isolating variety switches from derived switches and of considering product category–level factors as an explanation for the occurrence of variety-seeking behavior.
... Moderated Multiple Regression Moderated Multiple Regression (MMR) is an inferential procedure which involves of comparing two different least-squares regression equations (Aguinis, 2004;Aiken & West, 1991;Cohen & Cohen, 1983;Jaccard, Turrisi, & Wan, 1990). This study uses the MMR analysis to examine the moderating effect of size of organization on the relationship of INVC and PerLSP. ...
Logistics is a pillar industry to economic growth of every country. In current situation where developed countries are discussing and acting on sustainability initiatives to produce sustained performance in environmental, social and economic simultaneously, logistics organizations and their customers in some developing countries are still opt for traditional measures like service quality, delivery time and operational costs. Hence, through a questionnaire survey, this study examines the influence of administrative innovation capability on the performance of 81 logistics service providers (LSPs) in East Coast Malaysia on the performance of LSPs. Additionally, this study examines the moderating effect of organization's size on the relationship of administrative innovation capability and LSPs' performance. The results reported that the administrative innovation capability has a positive significant influence on their performance, but organization's size does not give any moderating effect to the relationship. The results are believed to provide guidelines to the logistics organizations to enhance their innovation capability as an effort to sustain in today's advanced market. It is recommended to add more dimensions of innovation capability and include sustainability measures for logistics performance in future research, as an extension of this study.
... This procedure is chosen given its theoretical appeal in cases in which the nature or specification of the interaction is unclear (i.e., might not be of the form X x Y). The usual criticism levied against subgroup analysis, that it is not recommended when the moderator permeates many parts of the model (Jaccard, Turrisi, and Wan 1990), is not encountered in this context. Moreover, though Ping ( 1995) offers a more parsimonious specification for the ...
Whereas some firms embrace and successfully exploit pro-social consumer influence strategies (e.g., environmental positionings, cause-related promotions), other firms tend to downplay their effectiveness and are reluctant to pursue such strategies. The author's research findings reveal that important moderators, namely consumer trust in the marketing source and attributions of consumer responsibility, must be activated for pro-social positioning strategies to work. Moreover, the levels of the moderating variables appear to be critical in determining whether a pro-social positioning strategy achieves the intended effect or backfires, thereby jeopardizing product equity and market share.
... The main effects of the independent variables (business guanxi, political guanxi and three MARKOR marketing orientation components) were entered into Model 2. Finally, we entered the interaction terms into Model 3. We tested for moderating effects by examining the change in R 2 attributable to the interaction terms added at the final stage. If a significant R 2 change appears for the criterion variable, then the moderating effect is judged to We collect industry information on an informal basis 0.56 We regularly review the likely effect of changes in our business environment (e.g., regulation) on customers We poll end users at least once a year to assess the quality of our products and services be significant (Jaccard et al., 1990). As demonstrated in Table III, the interaction models perform better than those containing the main effect only (change of R 2 value is significant) (Hair et al., 2010). ...
Purpose
Research focusing on the relation between market orientation and innovation in the Asian emerging economy is limited. The purpose of this study is to advance the extant literature by investigating the relations among market orientation, guanxi networking and innovation using the MARKOR scale.
Design/methodology/approach
The research conclusion is drawn based on the experience of 122 Asian emerging market firms operating in a wide variety of industrial sectors. This study explores whether the three MARKOR components (intelligence generation, dissemination and responsiveness) and their interaction with business and political guanxi have a significant effect on firms’ strategic innovation success. Innovation is measured following the practice of the OECD. In addition to the quantitative analyses, this study conducted qualitative interviews with executives of eight respondent firms, to further consolidate the subjects under investigation. The integration of both qualitative and quantitative data enriches the conclusions drawn from the study.
Findings
The findings of this study confirm that, when operating in an Asian emerging economy, both intelligence generation and responsiveness have a positive and direct impact on innovation. Though intelligence dissemination has no direct influence on innovation, its alignment with business and political guanxi still leads to a positive effect on innovation. The coalition of responsiveness and political guanxi, however, has a negative influence on innovation. The results of this study add new insights to the extant literature and provide implications for future research and marketing practices in Asian emerging economies.
Originality/value
The findings of this study confirm that, when operating in an Asian emerging economy, both intelligence generation and responsiveness have a positive and direct impact on innovation. Though intelligence dissemination has no direct influence on innovation, its alignment with business and political guanxi still leads to a positive effect on innovation. The coalition of responsiveness and political guanxi, however, has a negative influence on innovation. The results add new insights to the extant literature and provide implications for future research and marketing practices in Asian emerging economies.
... To model interaction effects, we add interaction terms for each additive combination of variables that are expected to influence each other's effects (Brambor, Clark, and Golder 2006;Jaccard and Turrisi 2003;Kam and Franzese 2007). We center all explanatory variables at their means. ...
This study addresses the conditions for the participation in protest activities. Starting from social psychological value expectancy theory and the theory of collective action, we study the effects of political discontent, perceived political influence (efficacy), norms to participate, identity, and membership in protest encouraging networks (“social incentives”) on protest. This study challenges the common assumption that these factors have additive effects only and provides a detailed analysis of interaction effects. Another contribution is the theoretical derivation of interaction effects. Our empirical analyses refer to the protests in Leipzig (East Germany) in 1989 under communist rule. Two‐way interactions are found between the following pairs of variables: discontent, influence, and norms. “Identity” (i.e., identification with West Germany) only interacts with discontent. Furthermore, identification is a surrogate for discontent: If identification is strong, discontent no longer influences protest. If identification is weak, increasing discontent raises protest.
... Moderated relationships are often called interaction effects (Cox 1984;Jaccard and Turrisi 2003). Interaction effects are most commonly considered in the context of regression analysis. ...
A variable annuity is a popular life insurance product that comes with financial guarantees. Using Monte Carlo simulation to value a large variable annuity portfolio is extremely time-consuming. Metamodeling approaches have been proposed in the literature to speed up the valuation process. In metamodeling, a metamodel is first fitted to a small number of variable annuity contracts and then used to predict the values of all other contracts. However, metamodels that have been investigated in the literature are sophisticated predictive models. In this paper, we investigate the use of linear regression models with interaction effects for the valuation of large variable annuity portfolios. Our numerical results show that linear regression models with interactions are able to produce accurate predictions and can be useful additions to the toolbox of metamodels that insurance companies can use to speed up the valuation of large VA portfolios.
... Moderated relationships are often called interaction effects (Cox 1984;Jaccard and Turrisi 2003). Interaction effects are most commonly considered in the context of regression analysis. ...
A variable annuity is a popular life insurance product that comes with financial guarantees. Using Monte Carlo simulation to value a large variable annuity portfolio is extremely time-consuming. Metamodeling approaches have been proposed in the literature to speed up the valuation process. In metamodeling, a metamodel is first fitted to a small number of variable annuity contracts and then used to predict the values of all other contracts. However, metamodels that have been investigated in the literature are sophisticated predictive models. In this paper, we investigate the use of linear regression models with interaction effects for the valuation of large variable annuity portfolios. Our numerical results show that linear regression models with interactions are able to produce accurate predictions and can be useful additions to the toolbox of metamodels that insurance companies can use to speed up the valuation of large VA portfolios.
... 1972). All other Race and/or Gender × Survey Year interactions test whether group-specific trends over time significantly differ from the group-specific trend for White men (see Jaccard and Turrisi 2003 for more information on interpreting interactions). 4 To coincide with these patterns, I present predicted probabilities across upper to lower bound of self-rated health (i.e. excellent, good, fair, poor health) and general happiness (i.e. ...
Despite progress in the status of Blacks and women over the past forty years, disparities in health/well-being persist. Using data from the General Social Survey, 1972-2012, I conduct a systematic assessment of U.S. differentials in self-rated health and happiness over the past four decades at the intersection of race and gender (White men, White women, Black men, Black women). In so doing, I provide new evidence regarding racial and gender dynamics in well-being since the civil rights and women's rights legislations of the 1960s/1970s and the extent to which racial-gender health inequalities have converged, diverged or remain unchanged. I find that well-being differentials across gender and race are generally converging; however, patterns are quite complex and contingent on gender, race and the specific outcome of interest. Black women for instance, present a consistent pattern of improvement. On the other hand, White women display a less consistent and paradoxical pattern. While White women report feeling healthier today than they were forty years ago, they are less happy with general aspects of their lives. Finally, White and Black men have experienced some changes in self-rated health and happiness over time, but their self-reports of well-being today, are nearly identical to their reports forty years with one exception. White men have experienced an overall pattern of decline in happiness in recent years following the great recession. I conclude with a discussion of what these patterns demonstrate regarding the changing nature of racial and gender inequality in the United States.
... In this paper, we check for the factors which affect cardiac disease mortality rate in a hospital. For this purpose, we consider the different IT applications used by a hospital, hospital characteristics, socio-economic factors and the interactions between IT applications and hospital characteristics and socioeconomic factors [39]. ...
The scope of healthcare information systems (HIS) is immense. It can not only help in providing easy access to data and taking decisions, but also ensure following standard procedures and improve quality. Prior literature have discussed on technology impact while controlling for the organizational and economic factors. However, there is a dearth of research on the effect of their interaction with technology. Moreover, overall technology impact misses the depth of application-level impact. Our work discusses the application-level impact and also empirically shows the effect of its interaction with other external factors. Our finding for 2010 show that use of HIS in nursing activities was significant in improving care quality. Disease-specific applications also have a positive effect under the influence of organizational factors. In 2013, per-capita income has significant effect on the impact of technology. Moreover our results show a considerable increase in the significance of technology and the interplay between technology and external factors in 2013 from that in 2010. Thus, our work motivates researchers to explore factors influencing the effect of technology. It directs managers to prioritize their investment on applications based on their impact on healthcare quality.
... Let us then turn to the trickier question of interpreting the model with interaction terms. As noted in the methodology literature (Jaccard and Turrisi 2003;Brambor, Clark and Golder 2006), once you include interaction terms in the model, the constituent variables can no longer be interpreted independently. To be more precise, the coefficient reported in the regression table only has that value when the other variable in the interactive relationship is zero. ...
Government instability (cabinet duration) is an important feature of parliamentary democracy. Over time, the research on cabinet duration has improved in technical and theoretical sophistication. However, we note that little attention has been paid to the relationship between governments and the state itself. Our main hypothesis is that state capacity, e.g., factors such as state bureaucratic effectiveness and law and order, shape how easy it is for governments to implement the new policy and thus how well they can achieve policy objectives. We also argue that when state capacity is low, the ability to adequately respond to external shocks goes down, and instability increases. When testing this empirically we find that low state capacity does indeed help us predict an increased risk for early termination—in particular, whether the government ends through a replacement (but not by an early election). Using interaction effects, we also demonstrate that the effect of external shocks, such as an increase in unemployment, is conditional on state capacity. An increase in unemployment only has a significant effect on cabinet stability when state capacity is low, suggesting that the cabinet’s (in)ability to address the economic problems is an important factor for understating cabinet durability.
... The moderated multiple regression (MMR) analysis was described as an inferential procedure in which two different least-squares regression equations were compared (Aguinis, 2004;Aiken and West, 1991;Cohen and Cohen, 1983;Jaccard et al., 1990). Using the MMR analysis, the moderating effect of the variable (product term) was analyzed by interpreting 1) the R² change in the models obtained from the model summaries, and 2) the regressions coefficients for the product term obtained from the coefficients tables. ...
... The high VIF scores of age and age squared pose no problems because this type of multicollinearity does not change the coefficients of the regression. The p-values remain unchanged even if altered to address the multicollinearity (Friedrich, 1982;Jaccard & Turrisi, 2003). There is, therefore, no harmful multicollinearity in the models specified. ...
en We draw on social capital and social vulnerability explanations to investigate the determinants of household emergency preparedness using data from the 2008 General Social Survey (GSS) and multivariate ordinal logistic regression. We develop an ordinal‐level scale for household emergency preparedness. We also create indices for individual social capital and risk perception, which correlate with higher levels of household emergency preparedness. We show that race and gender per se do not make households more or less prepared for emergencies because these variables are proxies for socioeconomic inequalities in society. Our study provides insights into household emergency preparedness and direction for policymaking.
摘要
zh 笔者通过使用有关社会资本和社会脆弱性的研究, 同时利用2008年⟪综合社会调查⟫和多因素有序逻辑回归分析的相关数据, 调查了家庭应急预备的决定性因素。笔者为家庭应急预备提出了一项有序的衡量。同时提出了用于个人社会资本和风险认知的各项指标, 这与更高程度的家庭应急预备有关。研究表明, 种族和性别从本质上并不会影响家庭的应急准备, 因为这些因素都是社会经济不平等的指标。本文为家庭应急预备和决策方向提供了见解。
Resumen
es Nos basamos en las explicaciones del capital social y la vulnerabilidad social para investigar los determinantes de la preparación para emergencias de los hogares utilizando datos de la General Social Survey de 2008 y la regresión logística ordinal multivariable. Desarrollamos una escala a nivel ordinal para la preparación de emergencias de los hogares. También creamos índices para el capital social y la preparación de riesgos, que corresponden a niveles más altos de preparación para emergencias de los hogares. Mostramos que la raza y el género en sí no hacen que los hogares sean más o menos preparados para las emergencias porque estas variables son indicadores de la desigualdad socioeconómica en la sociedad. Nuestro estudio proporciona información acerca de la preparación para emergencias de los hogares y también de la dirección a la que se dirige la creación de políticas.
... Follow-up analyses indicated that these effects were particularly pronounced for simple tasks. To investigate whether need for achievement moderated the effect of length of instructions on the outcome variables we performed four separate hierarchical regression analyses with identification, irritation, accuracy and productivity as separate outcomes, while controlling for background variables [69][70][71]. In the first step, we entered simultaneously the standardized scores of the control variables, need for achievement, length, complexity and the interaction term of length and complexity as predictors, while in a second step, the interaction term between length and need for achievement was added as a predictor (see Table 3). ...
For reasons of bureaucracy and safety, astronauts on the International Space Station are provided with excruciatingly detailed instructions and a lack of decision-making power, even for simple routine tasks. Besides being time-consuming, many astronauts report feelings of demotivation, irritation, and even defiance when confronted with this working method. Anecdotic evidence suggests that this method leads to situations where astronauts read instructions diagonally or avoid checking in with mission support, thereby ironically increasing the risk of error making. There is a need to consider under which circumstances, for whom, and why the provision of long instructions could be detrimental for well-being and performance. An experimental study with LEGO assembly tasks examined whether length of instructions (i.e. short versus long) and task complexity (simple vs. complex) impact negative affect, motivational experiences and performance of participants (N = 113, Mage = 18.75 ± 2.46 years). Long instructions for simple tasks provoked greater feelings of irritation, diminished the perceived value of instructions, and negatively influenced productivity and accuracy. The negative effect of long instructions on irritation was explained via decreased perceived value. Additionally, the effect of length of instructions on irritation differed for participants high versus those low in need for achievement.
... A series of hierarchical regression analyses (Jaccard et al., 1990) were conducted to examine the hypotheses, shown in Table 6. First, control variables, namely, age, work experience, and education were input into the regression models (Models 1 and 4). ...
Individuals’ unsafe behavior is commonly identified as an important causal factor in workplace accidents. Research has demonstrated the effect of work-related stress on work performance, while the effect of safety-related stress on safety performance has received little attention. This paper examined the predictive powers of safety-related stress and psychological capital (PsyCap) on safety behavior, and the moderating role of PsyCap on the safety-related stress–behavior relationship. Questionnaire survey data were gathered from 359 construction workers in China. Results showed that high safety-related stress would impair safety behavior in terms of safety participation (SP) but not safety compliance (SC). PsyCap’s positive influence on SC was stronger than that on SP. Furthermore, PsyCap moderated the relationship between safety-related stress and SP. For their sub-dimensions, it was found that (1) three selected safety-related stressors had negative influences on SP, while only safety role ambiguity had an effect on SC; (2) four sub-dimensions of PsyCap had stronger influences on SC than those on SP; (3) general PsyCap moderated the three safety-related stressors’ effects on SP; and (4) four sub-dimensions of PsyCap moderated the effect of general safety-related stress on SP. This research contributes to the conception of safety-related stress by demonstrating its validity and its negative effect on SP. It also contributes to the study on the mechanisms of SC and SP by clarifying the differential influences of safety-related stress and PsyCap and by considering their combined effects. Measures for improving SC and SP from the perspective of safety-related stress and PsyCap are discussed.
Understanding the interaction between habits and income can be an efficient way to economically improve income and this paper serves to figure out the effectiveness of health-related income factors and gender differences in these factors using regressions, interaction effects and fixed effect model estimations. I used China Health and Nutrition Survey (CHNS) for 2000, 2004, 2006, 2009, 2011 and 2015 and expected the study to be representative of the general population in China.
Results show clear effect of these factors, with that smoking can negatively associate with income and tea, coffee, alcohol, and exercising be in positive association. Also, gender differences are tested and interpreted. Extensions include discuss pathway through which these factors influence income, urban residence’s interaction effect with these factors and yearly differences.
Main findings are concluded for future possible uses, as policy makers for women’s economical empowerment programs may refer to the statistics and find the area that return the most such as drinking tea and quitting smoking.
This article compares cross‐national aging populations in Latin America to study the relationship between this population, regime type, and types of social expenditure. Much of the previous research addressed this relationship in industrialized countries, but those countries are predominantly democratic and have less variation in age demographics. I demonstrate that the effect of the aged population varies by regime type and type of expenditure. In general, democratic regimes with larger elderly populations spend more on social security and welfare. By and large, education policy is unaffected by the size of the elderly population regardless of regime type. These results suggest that the elderly population is most concerned with social security, which makes sense because these government expenditures directly affect them.
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An interaction in a fixed effects (FE) regression is usually specified by demeaning the product term. However, algebraic transformations reveal that this strategy does not yield a within-unit estimator. Instead, the standard FE interaction estimator reflects unit-level differences of the interacted variables. This property allows interactions of a time-constant variable and a time-varying variable in FE to be estimated but may yield unwanted results if both variables vary within units. In such cases, Monte Carlo experiments confirm that the standard FE estimator of x * z is biased if x is correlated with an unobserved unit-specific moderator of z (or vice versa). A within estimator of an interaction can be obtained by first demeaning each variable and then demeaning their product. This "double-demeaned" estimator is not subject to bias caused by unobserved effect heterogeneity. It is, however, less efficient than standard FE and only works with T > 2.
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Der Beitrag thematisiert einige methodische Fallstricke bei der Schätzung und Interpretation von linearen Regressionsmodellen mit Interaktionseffekten. Es wird gezeigt, dass bei der Interpretation von Haupteffekten in Interaktionsmodellen immer dann höchste Vorsicht geboten ist, wenn eine der an der Interaktion beteiligten Variablen keinen empirisch gültigen Nullwert aufweist. Auch wird gezeigt, welchen Einfluss die Entscheidung der Variablenskalierung auf die Schätzergebnisse haben kann und welche Interpretationsprobleme dabei auftreten können.
Multiplicative interaction models are widely used in social science to examine whether the relationship between an outcome and an independent variable changes with a moderating variable. Current empirical practice tends to overlook two important problems. First, these models assume a linear interaction effect that changes at a constant rate with the moderator. Second, estimates of the conditional effects of the independent variable can be misleading if there is a lack of common support of the moderator. Replicating 46 interaction effects from 22 recent publications in five top political science journals, we find that these core assumptions often fail in practice, suggesting that a large portion of findings across all political science subfields based on interaction models are fragile and model dependent. We propose a checklist of simple diagnostics to assess the validity of these assumptions and offer flexible estimation strategies that allow for nonlinear interaction effects and safeguard against excessive extrapolation. These statistical routines are available in both R and STATA .
In their pursuit of political influence, interest groups face the choice to contact policy elites directly or to generate pressure indirectly by appealing to the public at large. This article examines whether interest groups should prioritize inside or outside lobbying tactics in order to materialize their policy objectives, with a specific focus on European Union legislative policymaking. This article demonstrates that outside lobbying is not inherently more or less successful than inside lobbying; rather, the effect of inside or outside lobbying is conditional on the extent to which additional lobbying tactics are adopted and on the type of policy issues a lobbyist seeks to influence. The empirical approach of this article consists of an extensive media analysis and over 200 interviews with policy practitioners active on 78 policy proposals. The results indicate that outside lobbying leads to policy success when the lobbyist’s policy position enjoys popular endorsement within media debates and when the lobbyist engages in a coalition with other organized interests.
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An interaction in a fixed effects (FE) regression is usually specified by demeaning the product term. However, this strategy does not yield a genuine within estimator. Instead, an estimator is produced that reflects unit-level differences of interacted variables whose moderators vary within units. This is desirable if the interaction of one unit-specific and one time-dependent variable is specified in FE, but it may yield problematic results if both interacted variables vary within units. Then, as algebraic transformations show, the FE interaction estimator picks up unit-specific effect heterogeneity of both variables. Accordingly, Monte Carlo experiments reveal that it is biased if one of the interacted variables is correlated with an unobserved unit-specific moderator of the other interacted variable. In light of these insights, we propose that a within interaction of two time-dependent variables be estimated by first demeaning each variable and then demeaning the product term. This "double-demeaned" estimator is not subject to bias caused by unobserved effect heterogeneity. It is, however, less efficient than standard FE and only works with T>2.
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