This dataset has one predictor, one moderator, one control variable, one binary dependent variable, and a categorical variable.
Format
A data frame with 300 rows and five variables:
- dv
Dependent variable, binary: 0, 1
- iv
Independent variable, continuous
- mod
Moderator, continuous
- cov1
Control variable, continuous
- cat1
String variable with these values: "gp1", "gp2", and "gp3"
Examples
glm_out <- glm(dv ~ iv * mod + cov1 + cat1, data_test_mod_cat_binary, family = binomial())
summary(glm_out)
#>
#> Call:
#> glm(formula = dv ~ iv * mod + cov1 + cat1, family = binomial(),
#> data = data_test_mod_cat_binary)
#>
#> Coefficients:
#> Estimate Std. Error z value Pr(>|z|)
#> (Intercept) 24.36566 9.83244 2.478 0.013209 *
#> iv -1.83370 0.67576 -2.714 0.006657 **
#> mod -0.52322 0.19848 -2.636 0.008385 **
#> cov1 -0.02286 0.06073 -0.376 0.706562
#> cat1gp2 0.89002 0.36257 2.455 0.014100 *
#> cat1gp3 1.28291 0.34448 3.724 0.000196 ***
#> iv:mod 0.03815 0.01364 2.797 0.005163 **
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#>
#> (Dispersion parameter for binomial family taken to be 1)
#>
#> Null deviance: 415.03 on 299 degrees of freedom
#> Residual deviance: 390.91 on 293 degrees of freedom
#> AIC: 404.91
#>
#> Number of Fisher Scoring iterations: 4
#>