CAUTION: If you decide to use information from this app in a paper/manuscript, please make sure that you acknowledge that you have used this program by citing it. Also, should you decide to copy exact text, you will need to put quotes around that material to avoid plagiarism.

Stas, L, Kenny, D. A., Mayer, A., & Loeys, T. (2018). Giving Dyadic Data Analysis Away: A User-Friendly App for Actor-Partner Interdependence Models.
*Personal Relationships, 25*
(1), 103-119. DOI: 10.1111/pere.12230

CAUTION: If you decide to use information from this app in a paper/manuscript, please make sure that you acknowledge that you have used this program by citing it. Also, should you decide to copy exact text, you will need to put quotes around that material to avoid plagiarism.

Stas, L, Kenny, D. A., Mayer, A., & Loeys, T. (2018). Giving Dyadic Data Analysis Away: A User-Friendly App for Actor-Partner Interdependence Models.
*Personal Relationships, 25*
(1), 103-119. DOI: 10.1111/pere.12230

CAUTION: If you decide to use information from this app in a paper/manuscript, please make sure that you acknowledge that you have used this program by citing it. Also, should you decide to copy exact text, you will need to put quotes around that material to avoid plagiarism.

Stas, L, Kenny, D. A., Mayer, A., & Loeys, T. (2018). Giving Dyadic Data Analysis Away: A User-Friendly App for Actor-Partner Interdependence Models.
*Personal Relationships, 25*
(1), 103-119. DOI: 10.1111/pere.12230

*Personal Relationships, 25*
(1), 103-119. DOI: 10.1111/pere.12230

###
**Graphical Presentation of the Fitted Model**

###
*The full APIM figure*

The two figures presented below reflect all variables included in the model, also all covariates. If not all estimates are presented clearly, please try to diminish (or enlarge) the size of your browser. The figure will automatically adapt.

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**Standard model: **

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**Model with standardized parameter estimates: **

###
*The Basic APIM Figure*

The plots below show the basic APIM. Covariates and other requested parameters are estimated, but for simplicity only the estimates of the actor and partner effects are presented, together with the residual nonindependence in the outcome scores. In particular, the estimates, standard error and level of significance are shown. If two independent variables are taken into account the results for both are shown in separate figures. Please note this is done to facilitate the interpretation, but both predictors are indeed included in the same model at the same time.

###
*The Basic APIM Figure*

The two plots below are identical to the ones above, but only show the basic APIM. Covariates and other requested parameters are still estimated, but for simplicity only the estimates of the actor and partner effects are presented, together with the residual nonindependence in the outcome scores. In particular, the estimates, standard error and level of significance are shown.

####
**Standard model: **

** p < .05; ** p < .01; *** p < .001*

** p < .05; ** p < .01; *** p < .001*

####
**Model with standardized parameter estimates: **

** p < .05; ** p < .01; *** p < .001*

** p < .05; ** p < .01; *** p < .001*

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**Actor and Partner Effects**

The plots presented below are based on the fitted model. Thus, they take into account all estimated parameters.

The plot presented below is based on the fitted model. Thus, they take into account all estimated parameters.

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*First Independent Variable:*

####
*Second Independent Variable:*

*Personal Relationships, 25*
(1), 103-119. DOI: 10.1111/pere.12230

###
**Check Normality and Outliers**

In order to check the normality of the residuals, one can consult the following three plots.

*Guidelines for interpretation:*

- The density function of the residuals ideally looks bell-shaped.

- The boxplot should look symmetric around zero with limited number of outliers (or none at all).

- For the QQ-Plot, the dots should be situated on or close to the straight line.

###
**Effects in Raw Data**

The following plots are an exploration of actor (partner) effects, ignoring partner (actor) effects and the effects of plausible covariates.

It is important to know that these bivariate plots are strictly meant for data exploration because they do not represent pure actor (partner) effects from the APIM. Indeed, in the first plot the effect of one's own outcome on one's own predictor is not adjusted for the effect of the predictor of the partner, and hence does not strictly reflect the actor effect of the APIM. We therefore refer to these effects as 'semi-actor effects'. Similarly, the second plot rather shows the 'semi-partner effects'. To assess whether it is reasonable to assume linear effects of the independent variable on the outcome a smoother (i.e., a non-parametric best fitting curve) is added to the plots as a dotted line.

When one is interested in the estimated actor and partner effects of the fitted model, please consult the tab
*Figures*
.

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*First Independent Variable:*

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*Second Independent Variable:*

In the background, lavaan (i.e., an R-package for analyzing latent variables; Rosseel, 2012) is used. It is advised to save this lavaan script as a record of the analysis performed by the APIM_SEM app. This script allows to easily replicate the analysis afterwards, gives other researchers insight in your analysis and increases transparency.

The lavaan syntax can be directly copy-pasted into R for specifying a lavaan model. A step-by-step tutorial for first time R/lavaan users can be found in the tab
**Extra Info**
.

#### The basic APIM model

#### The APIM model correcting for unreliability

This model corrects for unreliability, based on the presumed reliability as entered in the 'Additional tab'. For more information on this process, please consult the paper ...