A mediation model with two predictors, two pathways,
Format
A data frame with 300 rows and 5 variables:
- x1
Predictor 1. Numeric.
- x2
Predictor 2. Numeric.
- m11
Mediator 1 in Path 1. Numeric.
- m12
Mediator 2 in Path 1. Numeric.
- m2
Mediator in Path 2. Numeric.
- y1
Outcome variable 1. Numeric.
- y2
Outcome variable 2. Numeric.
- c1
Control variable. Numeric.
- c2
Control variable. Numeric.
Examples
data(data_med_complicated)
dat <- data_med_complicated
summary(lm_m11 <- lm(m11 ~ x1 + x1 + x2 + c1 + c2, dat))
#>
#> Call:
#> lm(formula = m11 ~ x1 + x1 + x2 + c1 + c2, data = dat)
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -2.64294 -0.55585 0.08916 0.67243 1.70807
#>
#> Coefficients:
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) 2.13910 1.32319 1.617 0.109276
#> x1 0.35204 0.08946 3.935 0.000158 ***
#> x2 -0.04471 0.09540 -0.469 0.640340
#> c1 0.07961 0.10081 0.790 0.431666
#> c2 -0.09890 0.08790 -1.125 0.263356
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#>
#> Residual standard error: 0.9613 on 95 degrees of freedom
#> Multiple R-squared: 0.1679, Adjusted R-squared: 0.1328
#> F-statistic: 4.791 on 4 and 95 DF, p-value: 0.001453
#>
summary(lm_m12 <- lm(m12 ~ m11 + x1 + x2 + c1 + c2, dat))
#>
#> Call:
#> lm(formula = m12 ~ m11 + x1 + x2 + c1 + c2, data = dat)
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -2.4487 -0.6344 0.1066 0.5949 2.4585
#>
#> Coefficients:
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) 8.23329 1.38073 5.963 4.32e-08 ***
#> m11 0.45408 0.10562 4.299 4.18e-05 ***
#> x1 -0.21182 0.09931 -2.133 0.0355 *
#> x2 -0.07206 0.09832 -0.733 0.4654
#> c1 0.20391 0.10412 1.959 0.0531 .
#> c2 -0.42456 0.09109 -4.661 1.04e-05 ***
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#>
#> Residual standard error: 0.9896 on 94 degrees of freedom
#> Multiple R-squared: 0.3525, Adjusted R-squared: 0.318
#> F-statistic: 10.23 on 5 and 94 DF, p-value: 7.515e-08
#>
summary(lm_m2 <- lm(m2 ~ x1 + x2 + c1 + c2, dat))
#>
#> Call:
#> lm(formula = m2 ~ x1 + x2 + c1 + c2, data = dat)
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -2.25156 -0.62962 -0.02606 0.64273 1.67002
#>
#> Coefficients:
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) 7.19926 1.21769 5.912 5.28e-08 ***
#> x1 0.02233 0.08232 0.271 0.7868
#> x2 0.28901 0.08779 3.292 0.0014 **
#> c1 -0.13437 0.09277 -1.448 0.1508
#> c2 -0.01723 0.08089 -0.213 0.8318
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#>
#> Residual standard error: 0.8847 on 95 degrees of freedom
#> Multiple R-squared: 0.1167, Adjusted R-squared: 0.07948
#> F-statistic: 3.137 on 4 and 95 DF, p-value: 0.01805
#>
summary(lm_y1 <- lm(y1 ~ m11 + m12 + m2 + x1 + x2 + c1 + c2, dat))
#>
#> Call:
#> lm(formula = y1 ~ m11 + m12 + m2 + x1 + x2 + c1 + c2, data = dat)
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -2.52098 -0.63677 -0.04699 0.60540 2.05599
#>
#> Coefficients:
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) 7.44629 1.72403 4.319 3.95e-05 ***
#> m11 0.14694 0.10966 1.340 0.18354
#> m12 0.23402 0.09787 2.391 0.01884 *
#> m2 -0.43300 0.10894 -3.975 0.00014 ***
#> x1 -0.07840 0.09651 -0.812 0.41865
#> x2 0.00322 0.09875 0.033 0.97406
#> c1 0.04238 0.10188 0.416 0.67842
#> c2 -0.04145 0.09592 -0.432 0.66666
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#>
#> Residual standard error: 0.9391 on 92 degrees of freedom
#> Multiple R-squared: 0.2786, Adjusted R-squared: 0.2237
#> F-statistic: 5.075 on 7 and 92 DF, p-value: 6.688e-05
#>
summary(lm_y2 <- lm(y2 ~ m11 + m12 + m2 + x1 + x2 + c1 + c2, dat))
#>
#> Call:
#> lm(formula = y2 ~ m11 + m12 + m2 + x1 + x2 + c1 + c2, data = dat)
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -2.4153 -0.5711 0.1328 0.6137 2.2840
#>
#> Coefficients:
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) 10.98160 1.95311 5.623 2e-07 ***
#> m11 0.02417 0.12423 0.195 0.846185
#> m12 0.13525 0.11088 1.220 0.225649
#> m2 -0.43598 0.12341 -3.533 0.000645 ***
#> x1 0.11534 0.10933 1.055 0.294202
#> x2 0.06204 0.11187 0.555 0.580515
#> c1 -0.04905 0.11542 -0.425 0.671820
#> c2 0.04581 0.10867 0.422 0.674297
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#>
#> Residual standard error: 1.064 on 92 degrees of freedom
#> Multiple R-squared: 0.1526, Adjusted R-squared: 0.08818
#> F-statistic: 2.368 on 7 and 92 DF, p-value: 0.02857
#>