# Example Exercise: Regression (Frequentist)

## Solutions

Developed by Naomi Schalken, Lion Behrens and Rens van de Schoot

This tutorial expects:

• Basic knowledge of correlation and regression
• Any installed version of SPSS on your electronic device

This tutorial provides the reader with a basic introduction to the investigation of data relations using SPSS. Throughout this tutorial, the reader will be guided through importing datafiles, exploring summary statistics and relational analysis using correlation and regression analyses. Here, we will exclusively focus on classical frequentist statistics. To conduct Bayesian analyses in SPSS, click here for your Bayes tutorial!

Throughout this tutorial we will use a dataset from Van de Schoot, van der Velden, Boom & Brugman (2010). Using multiple regression, we will predict adolescents’ socially desirable answering patterns (sd) from overt (overt) and covert (covert) antisocial behaviour. For more information on the sample, instruments, methodology and research context we refer the interested reader to the paper (see references). Here we will focus on data-analysis only. The data set and syntax file can be found in the subfolders tilted 'Assignment Files' and ‘Solutions’.

Note: In many other "How to get started" exercises you will be asked to compare the results from here with results you can obtain e.g. in R or lavaan. Make sure to save or write down the results you found in this exercise.

### Preparation - Importing and Exploring Data

You can find the data in the file popular_regr_1.xlsx, which contains all variables that you need for this analysis. Although it is a .xlsx-file, you can directly load it into SPSS using the following settings.

Once you loaded in your data, it is advisable to check whether your data import worked well. Therefore, first have a look at the summary statistics of your data. You can da so by clicking `Analyze -> Descriptive Statistics -> Descriptives`. Alternatively, to construct a reproducible analysis, you can open a new syntax file by clicking `File -> New -> Syntax` and executing the following code:

```DESCRIPTIVES VARIABLES=respnr Dutch gender sd covert overt
/STATISTICS=MEAN STDDEV MIN MAX.
```

Question: Have all your data been loaded in correctly? That is, do all data points substantively make sense? If you are unsure, go back to the .xlsx-file to inspect the raw data.

### Exercise 1 - Correlation Analysis

In this exercise you will run a regression model with sd as outcome variable and overt and covert as predictors. But first, let's have a look at the bivariate (that is: pairwise) correlations between the variables of interest. You can obtain these by clicking on `Analyze -> Correlate -> Bivariate` or executing the following code in your syntax file:

```CORRELATIONS
/VARIABLES=sd covert overt
/PRINT=TWOTAIL NOSIG
/MISSING=PAIRWISE.```

Simply copy-paste these four lines into the new syntax file, select all text `Ctrl+A` and run the commands with `Ctrl+R`.

Question: What do the significance signs and magnitudes of the correlations tell you about the relationships between the dependent variable and its predictors? Are the independent variables themselves also associated with each other?

### Exercise 2 - Regression Analysis

Now, let's run a multiple regression model predicting socially desirable answering patterns (sd) from overt (overt) and covert (covert) antisocial behaviour. You can do so by clicking `Analyze -> Regression -> Linear` or executing the following code:

```REGRESSION
/MISSING PAIRWISE
/STATISTICS COEFF OUTS R ANOVA
/CRITERIA=PIN(.05) POUT(.10)
/NOORIGIN/DEPENDENT sd
/METHOD=ENTER covert overt.
```

Question: What do you conclude from the regression coefficients? Include the significance and relevance (R2) of effects in your answer.

Question: Have a look at the standardized regression coefficients. Are they different from the correlation results that you obtained in Exercise 1? If so, explain why!

### References

Van de Schoot, R., van der Velden, F., Boom, J. & Brugman, D. (2010). Can at Risk Young Adolescents be Popular and Antisocial? Sociometric Status Groups, AntiSocial Behavior, Gender and Ethnic Background. Journal of Adolescence, 33, 583-592.

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