This dataset has one predictor, one moderator, one control variable, one dependent variable, and a categorical variable.
Format
A data frame with 500 rows and five variables:
- dv
Dependent variable, continuous
- iv
Independent variable, continuous
- mod
Moderator, continuous
- cov1
Control variable, continuous
- cat1
String variable with these values: "gp1", "gp2", and "gp3"
Examples
lm_out <- lm(dv ~ iv * mod + cov1 + cat1, data_test_mod_cat)
summary(lm_out)
#>
#> Call:
#> lm(formula = dv ~ iv * mod + cov1 + cat1, data = data_test_mod_cat)
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -1987.03 -463.99 0.25 455.14 2152.48
#>
#> Coefficients:
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) 1488.568 4540.789 0.328 0.743
#> iv -46.545 300.046 -0.155 0.877
#> mod -6.530 45.372 -0.144 0.886
#> cov1 10.024 10.173 0.985 0.325
#> cat1gp2 -112.588 76.046 -1.481 0.139
#> cat1gp3 -53.106 75.126 -0.707 0.480
#> iv:mod 4.275 2.993 1.428 0.154
#>
#> Residual standard error: 681.1 on 493 degrees of freedom
#> Multiple R-squared: 0.6021, Adjusted R-squared: 0.5973
#> F-statistic: 124.3 on 6 and 493 DF, p-value: < 2.2e-16
#>