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Moderation - Science topic
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Questions related to Moderation
Dear research community
(bold: key element)
To analyze the question of moderated/mediated regression in clinical psychology:
whether score in questionnaire A at baseline
predicts the later score in questionnaire B (metric, different time intervals)
AND whether the predictive effect is different depending on the type of intervention administered after baseline (6 different types, categorial variables), I wonder which statistical techniques would be most suitable, (i.e. with possible moderation or even mediation by treatment type).
A basically found two options: Linear mixed models with t-tests, and moderated regression:
LMM: suitable for the question, whether there is a predictors effect of A on later B (with baseline score of A as independent variable (between subject), the time as independent variable (within subject), and the dependent variable the subsequent score of B), however, I did not find a proper solution for for the moderation/mediation aspect. Splitting the sample in the 6 categories, calculate effect size and compare them with t-tests? I don’t think so.
However, the alternative, a moderated regression analysis doesn’t seem to be more suitable for this, neither, as there are six treatment types (Type1, 2, 3, 4, 5, 6), and if I understand right, this would need 5 coding variables which I guess, would be too complex to be interpreted. But maybe I am wrong.
Do you have any experience and/or suggestions about best practices of the analysis of such questions?
I would appreciate any statement
Thank you, Fabienne
Which theory can be used in the context of metaverse experience and brand equity and 2 moderators and 2 mediators.
Has anyone done research specifically on employee commitment as it relates to retention/turnover over time?
I am completing some research and want to complete a moderation analysis (using PROCESS) to see whether 'age at adoption' moderates the relationships between my predictor and dependent variable.
My IVs and DV meet all parametric test assumptions (e.g., linearity, homoscedasticity, no multicollinearity, normally distributed, etc). However, I can see that 'age at adoption' is very positively skewed, with most children being adopted around one year old, and I am wondering if it is still appropriate to use this as a moderating variable, with it being non-normally distributed?
Any advice very much appreciated!
Hello Dear community
I am currently working on an article on sharing tourist experiences via ‘’eWOM’’ (electronic Word-of-Mouth) and its influence on travel intention. In this context, I am looking for a solid theoretical foundation to explore the moderating effect or identify a moderating variable that may influence the following relationships:
1. Between ‘’eWOM’’ and destination image,
2. Between ‘’eWOM’’ and travel intention.
thank you in advance for your valuable help and remain at your disposal for any additional information.
Sincerely,
I'm a student and trying to figure out what analytic method would be best for my research project.
I've got 4 IV's (all continuous), 3 DV's (all continuous), and 2 potential covariates.
The 3 DV's are likely to be related somehow, as they are different measures of the same concept (self-report measures of empathy, behavioural measures of empathy), so I've been tossing up multivariate multiple regression (or canonical correlation analysis). Would anyone be able to provide some information/resources on how to do this (e.g. any other assumptions from the usual linearity, normality, homoscedasticity, multicollinearity etc.; or issues to consider in the interpretation of statistical results; considerations of power or alpha level etc.)
My other question was that there is research shows that one of the covariates potentially acts as moderator between the IV's and DV's. Would I just include that as a moderator? If so, how would I do a moderation analysis with several DV's? Or would it be suitable just to include an interaction variable instead?
Hello,
Sorry this might be a bit of a basic question. For my research, I have three hypotheses. 1)., that NC predicts CA, 2)., that SPS predicts CA, and 3)., that SPS will moderate the relationship between NC and CA.
Originally, I was planning on using a regression to answer hypotheses 1-2, and a moderation analysis for hypothesis 3. However, I am now wondering at whether I can use the main effects in the moderation analysis to answer hypotheses 1-2.
Thank you,
Ross Tumulty.
Hi there,
I am trying to conduct a moderation analysis (Model1) using PROCESS for SPSS by Hayes.
I have an independent variable containing of three groups: 1 control group (1) + 2 test groups (2 and 3). I want to compare each test group with the control group, i.e. 1 vs 2 and 1 vs. 3. Can this be done using the multicategorial option?
I am uncertain whether the dummy variables created by PROCESS will take the control group AND the other test group as a reference category or just the control group.
Coding of categorical X variable for analysis:
Stimulus X1 X2
1,000 ,000 ,000
2,000 1,000 ,000
3,000 ,000 1,000
So can I conduct one analysis using this multicategorial option or do I have to create dummy variables manually and conduct two separate analyses?
Many thanks.
As Hayes (2022) notes, the technical challenges associated with conducting moderation analyses using latent variables make such analyses impractical—if not impossible, in my experience. This has led to the common practice of estimating direct (or main) effects and mediation relationships using latent variables, while conducting moderation analyses at the observed-variable level.
Recently, however, I have encountered several critiques of this practice, primarily asserting that it is invalid. Yet, I find no strong methodological basis for outright rejecting this approach. Hayes (2022) has already challenged the previously held assumption that statistically significant direct and indirect effects are prerequisites for conducting mediation, moderation, or moderated mediation analyses. This suggests that the analyses of direct effects, mediation, and moderation involve conceptually and technically distinct processes.
Given this, I wonder why using different methods to address fundamentally different analytical questions would be problematic.
References:
Hayes, Andrew F. (2022): Introduction to mediation, moderation, and conditional process analysis. A regression-based approach. Third edition. New York NY: The Guilford Press (Methodology in the social sciences).
"Investigating the Impact of Adoption-Induced Sibling Hierarchy Disruptions on Family Functioning and Externalizing Behaviors: The Unique Role of the Middle Child and Moderating Effects of Socioeconomic and Cultural Factors – A Public Health Perspective"
Hi everyone! I'm doing a conditional analysis with Hayes' model 7 (moderated mediation with moderation in the first path) using Hayes' PROCESS for R. But can't seem to be able to input my multicategorical independent variable (3 groups).
I've dummy coded it, but dont know how to proceed for the PROCESS.
Thank you for your attention.
The pellet is very sticky and will not go into solution. Can I vortex it? I need to add ~1ml of media to a pellet made from 10ml of lentil-X to get it to go moderately into suspension.
I am conducting research on the relationship between long-term loans and economic growth through the moderating role of economic freedom.
The problem is that data on economic freedom for Palestine is not available. Methodologically, is it acceptable to use the arithmetic mean of data from neighboring countries like Jordan, Lebanon, and Egypt through what is called the small area estimation methodology?
After I mixed Streptomycin Sulfate powder (which is white in color) in ddH20, I stored it in 4°C overnight. The next day, it turned what I can best describe as a moderately transparent orangish/brownish color. Is this considered to be normal?
I've never prepared this stock before so I'm not sure if this should happen. I don't know if it's still considered to be "safe" to use or if I should just prepare a new stock.
Is there any researcher who has set 5 categories of quality of life for the WHOQOL-Bref test? For example: score 0-20: very bad, score 21-40: bad, score 41-60: moderate, score 61-80: good, and score 81-100: very good.
Research Title
"Investigating the Impact of Adoption-Induced Sibling Hierarchy Disruptions on Family Functioning and Externalizing Behaviors: The Unique Role of the Middle Child and Moderating Effects of Socioeconomic and Cultural Factors."
Research Description
This study examines the psychological and behavioral effects of adoption on sibling dynamics, mainly focusing on the challenges faced by the middle child when family hierarchies and roles are disrupted. By analyzing family functioning and externalizing behaviors, the research explores how introducing an adopted child shifts established sibling roles, leading to potential identity conflicts, rivalry, or behavioral outcomes. Special attention is given to the moderating effects of socioeconomic status (SES) and cultural norms, which influence familial adjustments and coping mechanisms.
The research addresses a critical gap in adoption literature, where the middle child's unique challenges in adaptively renegotiating their role within a restructured sibling hierarchy remain underexplored. Furthermore, the study seeks to contribute practical insights for family counselors and policymakers to support adoptive families during transitional periods better.
Research Question (RQ)
Primary Research Question:
- How does the disruption of established sibling hierarchies and family roles due to adoption impact family functioning and externalizing behaviors, with a particular focus on the middle child, and how do socioeconomic and cultural factors moderate these effects?
Hello members!
My query concerns moderation analysis in PLS-SEM for SmartPLS 4 software users...
Currently, I am writing a research gap on a certain topic. I have found that three latent variables, X, Y, and Z, have been modeled differently in existing studies. Some studies have modeled the effect of X on Y, others Z on X, others Z on Y, and others Z moderated the effect of X on Y. My novel idea is to combine these variables in a single model (as shown in the attachment).
My question is, can I draw this model as it is in SmartPLS4 and proceed with validation and estimation, or are there steps that I have to follow? My main worry is the moderation part and mediation, as the X now takes the mediator position in this model.
Hi everyone, I ran a moderated moderation analysis using PROCESS model 3 in R with the variables X (predictor), Y (outcome), W (moderator 1), and Z (DV). I found significant interaction terms between X and W. However, when I used model 1 to explore the interaction terms between X and W, the results were not significant. Is there another model that could help me support my hypothesis? Also, why did the same predictor and moderator yield different results in model 3 compared to model 1?
Hi everyone
I am working on a project in which I am examining moderating role of timeframe on relation of a variable (self-compassion) on some other variables (such as anxiety). I think I need to utilize moderation analysis (using Process software), but problem arises as I have no score for timeframe. In fact I asked participants to answer two versions of self-compassion scale, one assessing self-compassion when participants think about facing difficult situation (state self-compassion) and other assessing self-compassion generally (trait self-compassion). It means that each version uses different timeframe, and now I want to test whether timeframe impact relationship of self-compassion with anxiety.
can you help me choosing right analytic strategy?
the bests
I hope you are all doing well.
While we were analyzing the data, we encountered some statistical issues. We would be very grateful if you could dedicate some time to addressing them:
1. Would we face statistical problems in our regression analysis if we had 14 predictors and 3 dependent variables? I am referring to Multicollinearity in regression analysis and related restrictions.
2. We checked the correlation of our moderator with each dependent variable, and they were all below 0.6. Based on our data and theoretical framework, do you recommend using that variable as a moderator?
I used the SPSS PROCESS program to investigate the role of the dichotomous moderator variable. In this work, there are 4 independent variables, one dependent variable, and one dichotomous moderator. But I don't know how to draw a table for the dichotomous moderator variable and its conditional coefficient. And report the results. If anyone knows, I would be grateful and appreciative if you told me.
Hi all,
I'm currently doing my masterthesis and I'm a bit stuck. My thesis researches the link between self-esteem and social relationships and how anxiety and depression influence this relation (a moderation). However, I can't seem te find any research to back-up my moderation. My hypothesis is that there's a positive relation between self-esteem and social relationships, but with higher scores of anxiety/depression, the relation weakens.
I do find enough research that indicate that there's a positive relation between self-esteem and social relationships - and that this relation can variate with other factors, such as age, gender or ethnicity. Just not anything about anxiety or depression.
What I also find are direct links between anxiety and self-esteem, anxiety and social relationships, depression and self-esteem, and depression and social relationships. Which all indicates that there's a negative relation between the variables.
So, my question is: how can I best justify my moderation?
Thanks in advance!
In our research, we did a linear regression analysis to understand the moderating impact of gender, it's evident that gender has a significant moderating impact, now I want to understand which gender had more moderating impact than the other. But I am not sure how that can be done in Jasp, it's an open-source tool for statistical analysis.
My independent variable is foreigner/citizen, moderator is gender, mediator is latent 'community acceptance' and dependent variable is latent 'happiness index'. How do I interpret results, given that a categorical independent variables delivers results which 'indicate differences' in smartpls4?
If there is a research model with one IV, one DV and one continuous moderator. So, how to check the parametric assumptions in SPSS?
Include an Interaction Term:
Create an interaction term by multiplying the IV and the moderator.
Run the Moderated Regression Analysis:
Set up a regression model where the DV is the outcome variable, and the IV, moderator, and interaction term are the predictors.
Check Parametric Assumptions for the Model
I have been reading a paper that evaluated the association between low, medium and high intake of certain food groups and risk of disease relapse. I am trying to understand the odds ratio results in the paper.
So my question is relating to table 4:
Doesn't an OR of 0.22 (p=0.007) for medium intake of processed meat and an OR of 0.31 (p=0.005) for total n-3 (in the paper's table 4) mean that processed meat and n-3 reduce risk of relapse when consumed in moderation? Or am I misunderstanding the stats?
Hi,
I want a list of journals with moderate or low impact factors that takes up research related to the field of bioinformatics and flavonoids? Can anyone help me?
Sucker fish create a havily damaged biodiversity in Buriganga river. If we use this fish for our purpose then its population may be moderate toll.
Can anyone tell me that which one is better for running categorical moderation: Process macro by Hayes or AMOS? I want to write a scientific article, is it necessary to draw a model in Amos? And the results related to the calculation or can the results be reported only with spss?
Hello all,
I am trying to run a moderation analysis using PROCESS Macro with continuous IV/DV and a categorical moderator (nationality). My moderator has three categories (China, Japan, Korea), but every time I try to run Process Macro, I get the following error message:
"ERROR: A variable specified as multicategorical must have at least three categories."
I have specified the moderator as "multicategorical" --> Indicator.
Can anyone help me troubleshoot this issue? Thank you!
Rather a technical question directed to the moderators of RG: What happened to the standard settings of "Home" on RG?
I'm experiencing the following: Since a couple of days It is not indicated any more when an update of potential interest (to me) was posted. I just have to assume that the last ones are still near the top of the list. In addition the number of updates has become very limited. Normally I receive some 10 to 20 updates per day, but now it's less than a handful.
I did not change my settings, but perhaps RG did. If you have recently experienced the same issue, just give a short reply.
'm working on a paper but got stuck at running Process Macro Model 11, as this model is not letting me run the model for three-way interaction. My model is attached here.
My IV is categorical (two-level)
DV- Continuous
Mediator-Continuous
(2) Categorical Moderators. Both have two levels
While running model 11, I'm getting problems with singularity in the data. SPSS is probably considering one of my Dummy variables as the other. Even though I've changed the codes of each dummy variable to 0-1, 2-3, and 4-5, the problem remains the same.
Please help me find out how. Below are the errors I'm getting while running Process Model 11.
Model : 11
Y : BA
X : Adv_app
M : BV
W : Psy_Dis
Z : SM_Gen
Sample
Size: 399
**************************************************************************
OUTCOME VARIABLE:
BV
SINGULAR OR NEAR SINGULAR DATA MATRIX.
>Error encountered in source line #480574
>Error # 12492
>An attempt has been made to use previously undefined matrix (or scalar).
>Execution of this command stops.
Matrix - 'B' is undefined
>Error encountered in source line #480574
>Error # 12322
>Right hand side of COMPUTE is undefined.. However, I saw many papers that used the same process model 7 with two levels or two categories of categorical moderators.
My study concerns social identity leadership and how org. identification is influenced through in-group and out-group variables from a resource perspective which infers how power is used in identity prototypicality. Since French and Ravens bases of power use coercive, legitimate, informational and other powers among referent power. Referent power is more attuned to have a role in my model. But can I use this dimension (referent power) of French and Raven's social power as a separate variable, more specifically, as a moderator?
In a pluralistic society with diverse traditions, personal beliefs, and religions, how an individual or a group of people should coexist can be accepted by all while still maintaining and applying their belief values correctly.
Hi, I have a set of hypotheses about main effects and a set of hypotheses about moderating effects. One of the main effects is insignificant (H rejected). Namely, Capability does not predict Fraud (in my data). However, the moderating hypothesis "Machiavellian personality moderates effect of Capability on Fraud" is significant. According to my calculation, the statistical power in my regression models should be good, therefore my findings reliable. Still, I am not sure how to interpret this situation. So MACH changes (negatively) the slope of CAP=>FRAUD. But there is no reliable slope! Operationalization of CAP and MACH is consistent with the literature; FRAUD is measured through a lab experiment. Any ideas on how to interpret this? Also, I had to run regressions with moderators without the main effects due to huge multicollinearity. So I have two sets of models, models with main effects (just IVs / IVs + controls) and models with moderators (just MODs / MODs + controls).
Dear profs and researchers:
In my model, I have a moderator which is moderating relationship between A and C, but at the same time, it also have direct influence to D. Can I ask whether it is possible or not?
Thank you.
Kind regards.
Maybe not moderating between constructivism and privilege heritability.
So I am doing my thesis on the relation between cyberbullying perpetration and life satisfaction and if physical activity is a moderator. But in my moderation analysis the interaction is non-significant but the conditional effects are all significant. Is physical activity a moderator? or not? And why yes or no?
I employed Process Macro Model 15 to investigate a moderated mediation effect. The moderating variable significantly influences the indirect effect (path B), but does not show significance on the direct effect (path C).
Would it be appropriate to conclude there is a moderated mediation effect based on these findings?
Hello guys, I Have a question, I have structural equation model with multiple mediators, 2 mediator variables are dummy and 2 are continuous. I also heard that there is different manners of running moderation analysis in different software.
In terms of dificulty, which software is less dificult to run SEM with multiple mediator variables? AMOS ou SmartPLS? And Why?
Thank you in advance.
Kind regards?
I ran Process (Model 7) for my research and I found a significant interaction on the A path. I tested for the indirect effect and got a significant indirect effect, but the index of moderated mediation was not significant. This result feels odd because I have an interaction on the A path. It is my understanding that this would mean I would have significant moderated mediation for the indirect effect, but this is not what I found. Does anyone have any insight into this?
I did a moderation analysis using SPSS and Process macro model 3, whereby the interaction between X Z W was not significant, but the interaction between X and Z was. I am confused in how to interpret this, could someone please help me get back a grip on this?
The moderator, language proficiency, is a continuous variable, but I want to categorize it. Thank you~
Hello,
I am writing a thesis where I want to test the moderation effect of 4 groups (that I transformed into 3 dummies), on the main impact of the independent variable on the dependent one. The 3 dummies are : Female Senior, Female Adult and Male Senior (the baseline being Male Adult). However, I do not know if I am allowed to just test the moderation of the 3 of them separately and just compare their coefficients or if I should put the 3 dummies together in PROCESS. If the latter is true, I do not know how to do this.
Could you please let me know if I should put the 3 of them together, and if so, how?
Thank you for your help!
Please some one explain is it possible to take a variable as a mediator between two variables and moderators between another two variables need justification .
Hi all, I am hoping to do a moderated mediation using Hayes's PROCESS Macro. The model is as follow:
IV: Binary 2 levels
DV: Binary 2 levels
W (mediator): Continuous 2 subscales
M (moderator): Binary 2 levels (Moderating the W-DV path and IV-DV path in the moderated mediation model).
I am intending to use Model 15 for my analysis.
In the case my DV has 4 levels (Not seek help, Formal Help Seeking, Informal Help Seeking, Both), is there any available model to handle this?
Appreciate your advice on this !!
I am working on a meta-analysis on framing with cultural-level moderators (e.g. Hofstede dimensions including Individualism-Collectivism and Power Distance) and moderators based on findings in the literature (e.g. health behavior function, behavioral frequency). While the potential mechanisms and theoretical basis of moderations would be different with different moderators, they are highly correlated (r > 0.70, or V > 0.50 for two categorical moderators). What are the possible ways to address the potential confounds between these moderators *in the context* of a meta-analysis? Let's say I find support for moderations with both Moderator A (p < .001) and Moderator B, I am not sure how to know if "significant moderation" of B is due to strong correlations/confounding relationship with A, or if both moderators are really meaningful moderators. Thank you. Would appreciate if there is (ideally R) open data/code/example.
Wir haben folgendes Design:
- AV: Akzeptanz von Algotithmen
- Es gibt drei Gruppen: a) ohne Hinweistexte, b) mit sachlichen Hinweistexten c) mit emotionalen Hinweistexten
- Die Probanden sollen die Akzeptanz von Algorithmen bei insgesamt zwanzig verschiedenen Szenarien angeben. Diese Szenarien haben jeweils eine Bewertung auf den Skalen Risiko (1=niedrig .. 5=hoch) und Kreativität (1=niedrig .. 5=hoch)
Gewünscht ist eine Auswertung, wie sich die Hinweistexte auf die Akzeptanz auswirken unter der Moderation von Risiko und Kreativität des Szenarios.
Der Faktor Hinweistext ist offenbar between subject mit drei Ausprägungen. Aber wie gehe ich mit den Faktoren Risiko und Kreativität um? Ist das eine Messwiederholung (ANOVA)? Wie berechet sich die benötigte Stichprobengröße?
Ich würde mich über sachdienliche Hinweise freuen.
I can't really wrap my head around this and maybe somebody can help me.
I conducted an experimental study with a 2x2 between-subjects design (n = 50 per condition). I have the following variables:
- Fixed factor 1 (dichotomous, experimental manipulation of stimulus)
- Fixed factor 2 (dichotomous, experimental manipulation of stimulus)
- DV (metric, a scale from the questionnaire)
- Covariate (metric, a scale from the questionnaire)
- Moderator (metric, a scale from the questionnaire)
I first ran the base ANOVA model with the following terms:
- Factor 1
- Factor 2
- Factor 1 * Factor 2
- Covariate
Nothing was significant. Out of curiosity, I included the moderator by adding the following terms in addition to the above:
- Moderator
- Moderator * Factor 1
- Moderator * Factor 2
- Moderator * Factor 1 * Factor 2
What happened is that Factor 1 * Factor 2 became significant (after being non-significant in the base model) as well as the three-way interaction Moderator * Factor 1 * Factor 2.
So the 2 issues I am struggling with are the following:
- Why did the interaction of Factor 1 * Factor 2 become significant (p = .036) even though it was not even close (p = .581) in the base model without the moderator?
- How do I make sense of the three-way interaction and how can I best report it?
For the two-way interaction, I guess that I would report the marginal means of the DV in the 4 conditions and plot them with lines. This option is provided by SPSS.
But for the three-way interaction, if I understand correctly, the above two-way interaction between experimental conditions is not uniform, but differs across various levels of the metric moderator (e.g., the two-way interaction might be reinforced/attenuated/reversed/non-significant at certain values of the moderator). But SPSS doesn't seem to offer an option to plot this in the ANOVA menu.
I know that the PROCESS macro by Hayes features conditional effects at -1 SD, mean, and +1 SD values of the moderator as well as Johnson-Neyman areas of significance. So I guess I would need something in this direction. Or am I mixing up things here?
Not only in regression, but also in ANOVA, it is crucial to center your continuous covariates (as in ‘A by B with covariate’). That is, when you also request interactions between such a covariate and a main effect in the ‘/design’-subcommand. Otherwise, it may indeed occur that a lower term interaction may become false significant through adding a higher term interaction, as you described. In fact, without centering, your results are nearly uninterpretable. The main purpose of centering is to make the main-effect terms and the interaction-effect terms independent of each other, so they can be evaluated separately. This is also crucial in ANOVA with covariates, and this has received far too little attention. Not centering will give you counterintuitive results, as you experienced already.
To see what a three-way interaction might look like in practice, I made an exaggerated example in Figure ‘Three-way interaction example.png’. To illustrate, the DV increases from A=1 to A=2 in the B=2 subgroup when the Moderator=1, but decreases in the B=2 subgroup when the Moderator=3. (The Moderator here is ‘continuous’, be it only with values 1, 2, and 3 for illustrative purposes). In other words, the interaction between A and B depends on a third factor, in this case the ‘Moderator’.
In ‘Annotated SPSS-syntax with three-way interaction.docx’ you may see how you can make a Figure at the values of Moderator = M-1SD and M+1SD (there is no need to study and use Hayes’ PROCESS to do this). The result is (again) that the DV in subgroup B2 increases from A=1 to A=2 when the Moderator is ‘low’ but decreases when the Moderator is ‘high’. The A*B interaction depends on the value of the Moderator (see: ‘Three-way interaction example with Moderator at M-1SD and M+1SD.png’).
How can I categorize the Adherence in Chronic Disease Scale data into ‘poor’ and ‘good’ adherence categories for the purpose of multivariate logistic regression analysis? the nature of ACDS questionnaire are low(0-20), moderate(21-26) and high adherence(>26) but i want to categories into two non adherence and adherence and i trying to categories >26 score is dherence and less than or equal to 26 non adherence but dherence much more low compared to non adherence
I want to research on the moderating role of anxiety trait levels (continuous) in the effects of type of reinstatement (independent variable, categorical) on fear avoidance behaviors. I cannot seem to find how to work with a categorical independent variable in a moderation analysis on SPSS and I was wondering whether I need to create dummy variables and run the typical moderation analysis or whether I should conduct a factorial ANOVA.
Thank you!
could u help me with a reference support categorize continuous variable as low, moderate and high low (1-2.33), moderate (2.34-3.67) and high (3.68-5).
Currently conducting a study titled: The Role of Living Arrangement in the Noise Exposure, and Attentional Control Among College Students: A Moderation Analysis.
We are in need of instrument that will assess the Noise Exposure of College Students in their Living Arrangement (Dorms/Bed Space/ Condo/ Share Accomodation)
Thank you so much!
Does anyone know what I have done wrong = error message PROCESS v 4.2 moderation analysis with categorical moderator... 'one of the categories contains only a single case?'
The moderation variable is categorical with 4 values... I have run this analysis before and it worked perfectly... where have I made my mistake please?
I found two different products, and for each product, I found a female and a male to sell them in different ways.
1. The respondents needed to answer the same questionnaire twice after the four sellers showing them the two different products.
2. I want to see the moderating effects (different products coded as 0 or 1 variable), but could not see the significant differences when respondents were facing the female or male sellers (coded as 0 or 1 variable as the antecedent) when purchasing two different products.
Specifically, I want to find out, for example, when selling the service products, female seller has greater influence than male seller. However, when selling the normal product, I want to figure out female seller's influence lower than the male seller.
I was wondering whether it was because of the moderator was not correct and I need to find a new moderator or I did not find the right method to run the analysis? I could not really see the influence was reduced.
I am trying 3-way interaction.
I would like to find an example of a paper that describes the results.
If I wanted to experimentally investigate the effect of information quality on rumour sharing intentions and the moderating role of information sharing motivation in this (we would manipulate information quality), could I measure information sharing motivation through a questionnaire (e.g., I share information on Weibo to show my personality), and would the different information-sharing motives (e.g., information-seeking, status-seeking, and entertainment, i.e., these three motives are three different moderating variables, and we allow for a person to have many different information-sharing motives) as independent variables to investigate their moderating effects.
Moderated Mediation in SPSS using Hayes Process Macro Model 59
I want to examine the relationship between school grades and self-esteem and was planning to do a linear regression analysis.
Here's where my Problem is. I have three more variables: socioeconomic status, age and sex. I wanted to treat those as moderation variables, but I'm not sure if that's the best solution. Maybe a multiple regression analysis would be enough? Or should I control those variables?
Also if I'd go for a moderation analysis, how'd I go about analysing with SPSS? I can find a lot of videos about moderation analysis, but I can't seem to find cases with more than one moderator.
I've researched a lot already but can't seem to find an answer. Also my statistic skills aren't the best so maybe that's why.
I'd be really thankful for your input!
I am constructing a multilevel model. To specify, I have two independent variables, one in Level 1 and another one in Level 2. The moderate variable and dependent variable are both in Level 2. Now, the moderate variable will moderate the relationship between independent variable 1 (Level 1), independent variable (level 2), and dependent variable (level 2). I checked some relevant papers and materials indicated this situation should use the MSEM method, the traditional method (MLM) cannot use it to the bottom-up relationship between variables. I just found some code for Mplus to construct a 1-1-2, 1-2-1 model, etc. However, I am not familiar to the Mplus because R is my majority analyzed tool. Hence, I want to ask is it possible for me to use R to construct model? Is there any package that I can use?
I am preparing the NAP Buffer described in Camacho-Sánchez et al., 2013. The protocol calls for dissolution of 700 grams of Ammonium Sulfate in 1L of water. This step is described as "taking hours" and should be done at "low to moderate heat", but I've had the buffer on a hotplate stirrer for more than 16 hours at 55°C and it still doesn't dissolve completely. Has anyone else had this problem? What temperature range do you use? How long does it usually take you?
Thanks!
Originally, I intended to conduct independent samples t-test and one-way ANOVA in SPSS for analysing my data. However, when I examined the normality of the dependent variable (DV) for checking their assumptions, it showed that my DV is highly skewed as the attached photo.
My DV is measured through an open-ended question and it is a continuous variable about participants’ predictions of the duration of an emotion, ranging from 0 to almost 300 unit. Sample size is around 1000.
Since the normality assumption is violated, I am wondering:
- Whether I should conduct (1) nonparametric tests instead (e.g. Mann-Whitney u test and Kruskal-Wallis H test) or (2) a generalised linear model (which allows for the DV to have a non-normal distribution) by specifying the model as gamma with log link instead? Or (3) conduct both but when reporting the results, I say something like “because the results are similar, I will only report the parametric ones” (which is the generalised linear model)?
- I am also interested in examining the moderating effect of a categorical variable on the relationship between a continuous IV and a DV. Therefore, even if the answer to question 1 is "conducting non-parametric tests", I still would like to know whether I can perform the generalised linear model and examine the interaction of the IV and moderator, even my DV is not normally distributed?
Thank you in advance for your advice.
I regress X to Y: ,direct effect (c)
M: mediator: I regress X to M (a), M to Y (b)
Total effect = c + a*b
now i introduce a moderator effect between X and Y
How i calculate the total effect with moderator and mediator effect
Hi all!
For my master's thesis, I am investigating the effects of movement on an exposure intervention for PTSD symptoms. PTSD symptoms were measured at pretest and posttest, and the participants were divided into 4 groups: Control, stationary exposure, exposure with acute movement and exposure with delayed movement.
For the analysis, I want to include the participants' movement habits as a moderator, and measure the differences in symptom reduction for the conditions that include movement, and those that don't.
I've been looking for an efficient way of conducting this analysis, and came across the MEMORE macro for SPSS, but I've also been thinking of attempting this with repeated measures ANOVA.
Which approach do you think would be more useful and efficient for the analysis?
Thanks in advance!
I am currently doing my dissertation with the following variables
IDV : Prejudice
DV : Team Cohesiveness
W : Ethical Climate
So I got the result as a significant moderation but the conditional effects and the graph is confusing to interpret.
I want to seek input on the idea of mindfulness as a moderator or a mediator.
Trait mindfulness if it exists is a trait and so is innate for the most part. It exists prior to an individual's experiences later in life. As such it should be considered a moderator that exists a priori. The idea of trait mindfulness as a mediator just doesn't seem correct. An IV causes the mediator which, in turn, causes the DV. How can something like a traumatic event cause trait mindfulness? I am thinking of the theoretical approach I am going to take in an upcoming analysis. I believe that I am going to argue trait mindfulness is a moderator. Any ideas or discussion on trait mindfulness as a mediator or moderator is welcome. I use the FFMQ to measure mindfulness.
"I am conducting advanced research to determine the extent of the influence of a church leader's competence on religious moderation."
hi, i'm currently writing my psychology dissertation where i am investigating "how child-oriented perfectionism relates to behavioural intentions and attitudes towards children in a chaotic versus calm virtual reality environment".
therefore i have 3 predictor variables/independent variables: calm environment, chaotic environment and child-oriented perfectionism
my outcome/dependent variables are: behavioural intentions and attitudes towards children.
my hypotheses are:
- participants will have more negative behavioural intentions and attitudes towards children in the chaotic environment than in the calm environment.
- these differences (highlighted above) will be magnified in participants high in child-oriented perfectionism compared to participants low in child oriented perfectionism.
i used a questionnaire measuring child-oriented perfectionism which will calculate a score. then participants watched the calm environment video and then answered the behavioural intentions and attitudes towards children questionnaires in relation to the children shown in the calm environment video. participants then watched the chaotic environment video and then answered the behavioural intentions and attitudes towards children questionnaire in relation to the children in the chaotic environment video.
i am unsure whether to use a multiple linear regression or repeated measures anova with a continuous moderator (child-oriented perfectionism) to answer my research question and hypotheses. please please can someone help!
My current study has almost 1000 responses. However, for one of the item I am interested in examining, it is not normally distributed (see attached image 1 for your reference). Since participants’ responses are really diverse on that item, so even removing some of the extreme outliers still cannot solve the problem.
I would like to run a moderation analysis using this item as the dependent variable. From different source of information on the Internet, I learned that normality should not be an issue for PROCESS macro as it provides the function to bootstrap.
From one tutorial, I saw that in order to not to care about the normality issue, we should select the “Bootstrap inference for model coefficients” option (see attached image 2 for your reference). However, from the other tutorials I read, they only mention about the number of bootstrap samples, without mentioning that we have to select the “Bootstrap inference for model coefficients” option. I tried to run the analyses with and without this option, and it changed from significant interaction effect of IV and moderator (when this option is not selected) to insignificant (when this option is selected).
I cannot really find the purpose of the “Bootstrap inference for model coefficients” option in Hayes's book or on the Internet, and I am also not really good at statistics. Therefore, I would like your help in the following:
- Is bootstrapping performed even if I did not select the “Bootstrap inference for model coefficients” option in SPSS PROCESS macro?
- If my dependent variable is not normally distributed, should I select the “Bootstrap inference for model coefficients” option to ensure more accurate results? If possible, can you also explain a little bit what this option is about?
Thank you in advance for your kind assistance.
I conducted moderation with age as a moderator, using PROCESS. the age range is 65-91. the program cut the age groups as follows: 67, 74, 82. what does it actually mean? If this means: group 1: participants between 67-74, group 2 =74 -82, group 3 above 82, then the participants between 65-67 were not included? (only 3 groups were created).Thank you
Do you have recommendations for a professional grade model that 1) can sustain moderate flow velocities (up to 1,5 m/s) and 2) has a wide angle optics?
Thanks
I am a bit confused about the interaction effect of a two-way ANOVA and moderation.
Example:
For example, I want to examine how the intensity of exercise (i.e. 1 = walking; 2 = running) affects the amount of calories burned. I suspect that higher intensity exercise (i.e. running than walking) lead to more calories burned. However, I suspect that the gender of the participants may also have an effect. For example, among male, higher intensity exercise should lead to more calories burned than female.
In this case, should I use (1) two-way anova, and see whether the two independent variables (i.e. "intensity of exercise" and "gender of the participants") have a significant interaction effect; OR (2) moderation analysis using PROCESS Macro of SPSS and see whether the interaction term of the independent variable (i.e. "intensity of exercise") and the moderator (i.e. "gender") is significant?
My confusion:
To me, it seems that no matter which analyses, as long as it gives me a significant result, I can still interpret the result the same way, and answer my hypothesis. Therefore, I would like to know the rationale in choosing which analyses to use in similar cases. Is it related to the nature of my variables (i.e. categorical/ continuous) or are there other reasons?
Can anybody help? Thank you.
I am analysing a set of data which have both within-subject and between-subject variables. However, since my assigned task is just simply focusing on part of this data set, I am not interested in examining the within-subject variable.
To make you understand it easier, here is an example:
The original study is to examine how the branding of the product (independent variable) affects participants' happiness (dependent variable), and all participants are required to try both brand A and brand B product. However, extending from this original study, I was asked to examine how participants' demographic may actually affect their happiness instead.
My questions are:
- Can I run a mixed model ANOVA and only focus on the main effect of the between-subject variable while ignore the main effect of the within-subject variable and the interaction effect? Is this an acceptable way to analyse the data for academic publication?
- Since participants are required to try both brand A and brand B product, my dependent variable is recorded by two separated columns in the data set (one for brand A's dv and another for brand B's dv). So, what should I do if the analyses that I want to run does not allow me to specify the within-subject variable. Even if I use the "restructure" function in SPSS and make the dependent variable to be in one column only, I still cannot run the analyses as it violated the assumption of the test (e.g. independence of observation) and make the results less reliable. For example, I want to run the moderation analyses using PROCESS Marco in SPSS, but it only allow me to put one item in the dependent variable option. I can restructure the data, so that my dependent variable would only be in one column. However, I still cannot run the analyses as it violated the assumption of independence of observation. In this case, what should I do?
How can I solve these problems using SPSS? Can anyone help? Thank you
Hi! I am trying to analyze a moderated mediation using mplus. I first started with a simple mediation, so X -> M -> Y. Path a (X -> M) is not significant, while Path b (M -> Y) is significant in the simple mediation (p=0.004).
However, when I introduced the moderator, it was found that Path a becomes significant (p=0.011), but Path b becomes only marginally significant (p=0.066), and the moderating effect is also significant (p=0.048). While of course it is good to see that the moderating effect is significant, I wonder why path b would become insignificant in my moderated mediation model? It is quite a big jump from p=0.004 to p=0.066, so it is really weird to me. Is it because Mplus allows the paths a and b to covariate? If so, are there any ways I could relax such default constraint and see the effect?
Any suggestions or recommended readings on this are highly appreciated!
Many thanks!
Sure! Please find below the input in Mplus for your reference.
Input for MODERATED MEDIATION. I have done experiment, so the X1, X2, and Mo are all categorical variable, with only 0 and 1. Me1, Me2, and y1 are continuous. Me1 and Me2 are two parallel mediators, and I moderate the first paths from X1 to Me1 and X2 to Me2. The other moderated mediations are just to control their effects.
Define:
! Predictor variable - X1, X2
! Mediator variable(s) - Me1, Me2
! Moderator variable(s) - Mo
! Outcome variables - y1
X1=INSupp;
X2=EMSupp;
Mo=Climate;
Me1=Threat;
Me2=Justice;
y1=AcceptH;
CENTER X1 X2 Mo (GRANDMEAN);
Inter1 = X1*Mo;
Inter2 = X2*Mo;
VARIABLE:
names = Climate Support INSupp EMSupp Warmth Sincere Threat
Shame Justice AcceptH WHelp Leave Involve Realism;
missing = all(99.99);
usevariable = X1 X2 Mo Me1 Me2 y1 Inter1 Inter2;
! Standard deviation of W = 0.497
ANALYSIS: TYPE = GENERAL;
Estimator = ML;
Bootstrap = 5000;
! In model statement name each path and intercept using parentheses
MODEL:
y1 on Me1 (b11)
Me2 (b21)
X1
X2
Mo
Inter1
Inter2;
[Me1] (a0);
Me1 on X1 (a11)
X2 (a21)
Mo
Inter1 (m11)
Inter2 (m21);
Me2 on X1 (a12)
X2 (a22)
Mo
Inter1 (m12)
Inter2 (m22);
MODEL CONSTRAINTS:
! X1*W on M1
NEW(modh1 modl1 modd1);
modh1=a11+m11*0.497;
modl1=a11-m11*0.497;
modd1=modh1 - modl1;
! X1*W on M2
NEW(modh2 modl2 modd2);
modh2=a12+m12*0.497;
modl2=a12-m12*0.497;
modd2=modh2 - modl2;
! X2*W on M1
NEW(modh3 modl3 modd3);
modh3=a21+m21*0.497;
modl3=a21-m21*0.497;
modd3=modh3 - modl3;
! X2*W on M2
NEW(modh4 modl4 modd4);
modh4=a22+m22*0.497;
modl4=a22-m22*0.497;
modd4=modh4 - modl4;
! Moderated mediation
! X1*W on M1 on Y
NEW(momeh1 momel1 momed1);
momeh1=a11*b11 + m11*b11*0.497;
momel1=a11*b11 - m11*b11*0.497;
momed1=momeh1 - momel1;
! X1*W on M2 on Y
NEW(momeh2 momel2 momed2);
momeh2=a12*b21 + m12*b21*0.497;
momel2=a12*b21 - m12*b21*0.497;
momed2=momeh2 - momel2;
! X2*W on M1 on Y
New(momeh3 momel3 momed3);
momeh3=a21*b11 + m21*b11*0.497;
momel3=a21*b11 - m21*b11*0.497;
momed3=momeh3 - momel3;
! X2*W on M2 on Y
New(momeh4 momel4 momed4);
momeh4=a22*b21 + m22*b21*0.497;
momel4=a22*b21 - m22*b21*0.497;
momed4=momeh4 - momel4;
OUTPUT: Tech1 Tech3 Tech8 Cinterval(BCBOOTSTRAP);
PLOT: TYPE=PLOT2;
I'm still learning and confusing to choose which method to use for my study. What is the simple method should i use if i have 3 independent variables, 1 moderate and 1 dependent variable
Which Hayes model can we use to test parallel mediation in which the moderator only affects one of the mediation paths?
I am completing my thesis on the potential moderating effect of parent social media use frequency on parent-child communication and family functioning. Literature has indicated relationships between all variables however my correlation matrix does not show any significant correlations.
However, upon running my moderation analysis in SPSS with the Process macro I have found no significant interaction effect but there is a significant effect between social media use frequency (moderator) and family functioning (DV).
Can I confirm my study found a relationship between social media use frequency and family functioning despite the correlation matrix not supporting the findings of the moderation?
Despite my hypothesis that my moderator would be significant being unsupported it would still be great for my study if social media use frequency was shown to be related to family functioning. Past studies had not measured one specific aspect of social media as I have here so this could be an opportunity for future research recommendations.
No one has the mental capacity to know all languages. Additionally, the more languages one is fluent in, the more likely that individual will mix up words. Thus, knowing enough languages for survival is optimal while artificial intelligence could and potentially will bridge language barriers. Of course knowing three languages or more is somewhat of an advantage.
I am researching the relationship between social media and the sexual behaviour of secondary school students. One of my null hypotheses is that "There is no moderating impact of sex in the relationship between social media and sexual behaviour"
What method of analysis can I use? and how do I go about it
I am working on a research article about the effects of infant sleep problems on mothers’ well-being and how self-efficacy moderates this relationship. I have three independent variables, which are actually three subscales of the BISQ questionnaire. This questionnaire examines the sleep patterns of infants from 0 to 36 months. Its three subscales are infant sleep, parental perception, and parental behavior. My moderating variable is maternal self-efficacy. I also have six dependent variables: mother’s depression, anxiety, stress, life satisfaction, happiness, and sleep quality, which were measured with 4 questionnaires. For the statistical analysis of my findings, I performed 18 moderator analyses using the Process macro in SPSS, considering three independent variables, one moderating variable, and six dependent variables. However, I am not sure if this is a common or appropriate approach. I have not found any similar articles that do this. Are there any other multivariate techniques that I could use? How can I choose the best data analysis strategy for my research problem? Thank you for your help.
Is there a table that indicates the intervals at which soil is classified as low, moderate, or high compaction?
- is It statistically true to have a direct relationship between moderator variable and independent variable ?and between moderator and dependent variable? Of course in addition to its effect on the main relationship DV and IV?
I am a PhD student, and my thesis is on supply chain resilience. My model includes four independent variables, one moderator, and one dependent variable. The moderation in my model represents my main PhD contribution (my study novelty). Data analysis revealed non-significant moderation with 201 usable responses.
In a second trial to improve the results, I've collected additional responses and ended up with 299 usable responses. However, the data analysis still showing non-significant moderation?? I've already done proper data cleaning and screening (missing data handling, normality, outliers, CMB, etc.). My questions:
1. Is there any advice to improve the results? get significant moderation.
2. From a PhD point of view, is there any risk of having such findings at the time of the upcoming VIVA Voce? especially that the non-significant moderation is my main contribution.
Appreciate your input
Emad
Hello
I want to conduct moderation analysis using the DEFINE command, categorical variables, cluster variable, and the WLSMV estimator. However, when I calculate the moderation analysis with these commands, analysis did not work.
I am just wondering whether I can use WLSMV estimator rather than ML or MLR to calculate the moderation analysis using DEFINE command in Mplus.
Thank you in advance.
Do you still believe that forgetting someone's Signature is a crime in the USA?
Fifth Press Release – Third Crime Report
December 11, 2023
Documentary Books series: Collective Injustice (Wells Fargo)
Fourth Book -- Wells Fargo: a symbol of denial and irresponsibility
Second Crime Report Title: Wells Bank Involvement in Illegal Affairs: Forged Signature at Wells Fargo
Please read the story at the end of this Crime Report.
Who Involved: Wells Fargo Bank Illegality, Ex-Wife, Family Court, Lawyers
Dates: During 2012
Discovered in 2018 by pure chance.
Damage and Impacts: A bad reputation with the bank, loss of time and money, and effort with adverse effects are catastrophic for me, my business, and my health. The damage and impacts are still continuous.
Legal and Principal Parties
1) My ex-wife, Madam Raefa Mostafa Al-Mehelmy, whom I divorced in Egypt in January 2018 and has been separated from in an unfair California family court for almost six years now.
2) Wells Fargo, in which all my personal and commercial accounts are in which all bank transactions
3) The family court is very unfair and harsh in dealing with American citizens of Arab or Islamic origin
4) Notorious credit bureaus Sub-legal parties
Sub Legal Parties:
2 Lawyers in California and 3 Lawyers in Egypt
In one of my visits to the bank at the beginning of 2012، a deputy Waverly Branch OF WELLS FARGO, PALO ALTO, I opened a Visa Card account because I am one of the excellent customers in the bank. I told her I agree.
She said - We will know in just one minute. The response came with a refusal. We were surprised. I asked her to look for the reasons. Of course, the bank refused to know what the real reasons were against the bank's refusal and the intervention of the head of the branch, and with my strong insistence on knowing the reason for this very harsh refusal. Although I accepted that refusal, I learned from my life in America that refusal occurs in a semi-normal way with American citizens of Islamic and African origins as forms of legalized racism in most cases, unfortunately.
The vice president was in a challenging situation, and she referred me to another person in the bank to look behind the bank's denial. And in a very short time after, he drew himself and his arrogance on him. I saw a document with signatures on it. And he asked me with rudeness and false arrogance - are these your signatures? I told him: The signatures are not my Signature. I almost exploded from rage and held firm. He let go of the false arrogance and said to me in a moderate voice - Can you sign your signatures on a piece of paper so that I may recognize your Signature? I told him: The bank has my Signature. I said it to God alone and drew my Signature. He adjusted and said I am very sorry because you have an old problem with the bank. They opened two accounts for you and your wife a long time ago (my ex-wife was in Egypt in January 2018), and they have signatures other than your signatures in your house, which do not match your signatures now as well, and I am not able to give you the documents. I erupted, became mad, and asked the police to visit the bank. The bank's vice president realized the situation was not in the bank's favor.
I mean, I have been living with a filthy demon since 2012. No morals. There is no creed, no origin, and all my thoughts are on my children and grandchildren after me, God willing. And I screamed at the top of my voice, and my heart cried and told them that this is a significant crime as we know it in America.
I tried to get the documents from the vice president of the bank, who spoke urgently with the central bank and told them that I insisted on calling the police to prove the incident. I took a copy of it with the accounts with a forged signature on it and asked her what had happened with the bank employee. She said the bank fired her - I took the documents and left, sadness and sorrow fill my heart, and the rest will come, God willing, soon.
God suffices me, and He is the best agent.
Important Alert
The purpose of writing this press release is not to offend any person, institution, group, political party, government, or country in the world. Instead, the purpose is to report and tell what befell me of wrong lest my experience would be repeated with others. It is intended to keep the stability of the community and guarantee the protection of its members, whether native or expatriate. It is a cry from me so that it may reach the ears of the world. Perhaps someone will hear it and help me to restore my lost and stolen rights. I intend to mention the names of some people who have done me wrong. I am not against any person, institution, government, or political party, but I am against any corruption or transgression by some irresponsible individuals who do not fulfill the role assigned to them appropriately. This is only for your information.
Contact information
AEEH PRESS INC
P.O. Box 21514
San Jose, CA 95151, USA
Fax – 408-984-3886
A Forged Signature is a Chapter 11 in
Volume 01: The Tale of an Egyptian with an American Passport
Extended and many crimes have been generated because of the forged Signature.
Volume 02: Our government, with its Institutions in California, neither Listens nor Cares
Volume 04: Wells Fargo: a Symbol of Denial and irresponsibility
Volume 08: Laws of the Jungle
Volume 17: Fake Judges, Lawyers, and Paralegals Driver of Corruption in Egypt and the USA.
Volume 19: Divorce and Family Court: Insidiousness, Malice, and Playing with Fire.
Volume 25: Divorce and Family Court: Worst Extortion and theft of my Wealth Unjustly.
Volume 26: Divorce and Family Court: Ugly Events from in and out of Family Court Room #77
Chapter 11: A Forged Signature
"The husband is the last one to know" is a French proverb. Although I am of Egyptian origin and live in America, this proverb applies. I say this because I only learned what my wife (now my ex-wife) did in 2012 by pure coincidence in 2018. Raefa Mustafa Al-Mehelmy was divorced in Egypt and is still separated from me before the "unfair" California Family Court. On one of my visits to Wells Fargo Bank, which contains all my personal and commercial accounts, at the Palo Alto branch, the Vice President of the Bank spoke to me about opening a Visa Card account, especially since I am one of the privileged customers. I agreed, and we began the usual procedures. Then, the response was confronted by a refusal. I asked her to let me know the reasons for the denial, but the bank management refused to disclose the cause. The head of the branch intervened, but it was in vain. I insist on finding out the reasons and opinions for this unfair refusal, despite my prior knowledge of the rejection caused by racism that was taking place against Americans of African and Islamic origins. Because of hateful and legalized racism, the bank's vice president is in an unenviable position. She referred me to another employee to discuss the reasons behind this unjustified refusal. In his office, I saw a document in front of him with many signatures. He tried to show off himself with arrogance.
Showing a grudge and malice, he asked," Do these signatures belong to you?" I categorically denied it and said that my signatures were forged. He asked me after he had given up his arrogance and spoke moderately:" If you, please put your Signature approved by the bank on this paper?" I told him that they had my authorized Signature already. However, in the end, I submitted to his request and put my Signature on a separate paper. After that, he said, "You have an old problem with the bank because of opening two accounts for you and your wife (my ex-wife now). We have papers with signatures that do not match your Signature." He pointed with his hand to the paper on which I drew my Signature. I tried to get a copy of these papers, but he refused vehemently, which forced me to break my calm, raged, and went crazy. I demanded that the police come to the bank. The bank's vice president sensed the situation's seriousness, and it was not in the bank's interest. Therefore, he acquiesced and gave me a copy of the documents with the forged signatures. I took the papers and left with a worn-out heart squeezed by grief and despair. What lousy luck put in my path this devil whom I honored by marrying and raising her family's status and hers, my ex-wife, Raefa Mustafa Al-Mehelmy. That woman has no morals, belief, origin, or loyalty to a man who does not fault that he trusted her and entrusted her with his money, house, and children.
I've often seen the following steps used to test for moderating effects in a number of papers, and I don't quite understand the usefulness of Model 1 (which only tests the effect of the control variable on the dependent variable) and Model 4 (which only adds the cross-multiplier term of one of the moderating variables with the independent variable). These two models seem redundant.
I need to add both moderator and mediator in case I miss it.
Hi everyone, I'm using PROCESS model 1 to explore the direct effect of continuous variable X and the moderation effect of continuous variable W on the association between continuous X and Y. However, the data didn't meet with the assumption of normal distribution. Should I continue to carry out the model or replace it with other methods?
There are two ways we can go about testing the moderating effect of a variable (assuming the moderating variable is a dummy variable). One is to add an interaction term to the regression equation, Y=b0+b1*D+b2*M+b3*D*M+u, to test whether the coefficient of the interaction term is significant; an alternative approach could also be to equate the interaction term model to a grouped regression (assuming that the moderating variables are dummy variables), which has the advantage of directly showing the causal effects of the two groups. However, we still need to test the statistical significance of the estimated D*M coefficients of the interaction terms by means of an interaction term model. Such tests are always necessary because between-group heterogeneity cannot be resorted to intuitive judgement.
One of the technical details is that if the group regression model includes control variables, the corresponding interaction term model must include all the interaction terms between the control variables and the moderator variables in order to ensure the equivalence of the two estimates.
If in equation Y=b0+b1*D+b2*M+b3*D*M+u I do not add the cross-multiplication terms of the moderator and control variables, but only the control variables alone, is the estimate of the coefficient on the interaction term still accurate at this point? At this point, can b1 still be interpreted as the average effect of D on Y when M = 0?
In other words, when I want to test the moderating effect of M in the causal effect of D on Y, should I use Y=b0+b1*D+b2*M+b3*D*M+b4*C+u or should I use Y=b0+b1*D+b2*M+b3*D*M+b4*C+b5*M*C+u?
Reference: 江艇.因果推断经验研究中的中介效应与调节效应[J].中国工业经济,2022(05):100-120.DOI:10.19581/j.cnki.ciejournal.2022.05.005.
I am doing my PhD thesis, and moderation is the main contribution (novelty) of my study. However, the study findings revealed non-significant moderation. R2 with moderation is 69%, while R2 without moderation is 68.5%.
I have two questions:
Would such findings impact my PhD thesis defense?
How can I justify such non-significant moderation?
Thank You.
Where is the point of ethical moderation between being excessively empathetic and being too self-interested?
IV: categorical - (5 categories with 1 and 5 being the extreme indicators)
DV: binary - (dummy coding has been done.)
Mo: continuous
1) Is it possible to use SPSS PROCESS MACRO for moderation analysis?
2) If so, would using the Johnson-Neyman technique be the right approach?
3) If using PROCESS MACRO is not appropriate, what method can I use to test moderation?
Hello everyone,
I have conducted moderated mediation analysis using model 14 from Hayes PROCESS for SPSS. I have grades as independent variable, satisfaction as mediator, extroverted as moderator and engagement as dependent variable.
The interaction effect between the moderation and mediation is significant, and the entire model for the moderated mediation is significant. However, my concern is about the effect of the mediation (satisfaction) on the dependent variable (engagement) that it is NOT significant.
What does this mean for my interpretation of the model? Since satisfaction (M) didn’t have a significant relationship with engagement (Y) (β=-0018, p=0.990), is it a problem? Can I still interpret that there is a moderated mediation effect? and accept the hypothesis? or I should reject the hypothesis?
p.s: in a separate model (4), satisfaction showed a mediating effect between grades and engagement.
For more details, you could see in the attached photos the results of my analysis.
Thank you so much for your help,
Talal
Hello, I want to test my serial mediation model with two moderators but no such template is available in PROCESS. How should I do it ? Kindly help?
a) A significant amount of time
b) A considerable amount of time
c) A moderate amount of time
e) Very little time
