README.md

In masurp/pmstats: Customized Functions for Statistical Computations, Result Extractions, and Reporting

pmstats

This package includes some custom-made functions to facilitate some common statistical procedures as well as extracting and reporting results from various models in RMarkdown articles. Please note that most functions are highly costumized to my personal workflow. They may hence break in more general frameworks or when used in a different, non-intended way…

Dependencies

Most functions require the following packages:

• For data wrangling procedures: tidyverse and magrittr
• For printing and typesetting: papaja
• For SEM procedures: lavaan and semTools

These packages should be installed prior to using this package.

Installation

You can install the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("masurp/pmstats")

Some examples

Printing a zero order correlation table

library(pmstats)
(tab <- zero_order_corr(mtcars[,1:6], 
                        digits = 2, 
                        sig = T, 
                        print = T))
#>   Variables      M     SD     1     2     3     4     5
#> 1     1 mpg  20.09   6.03                              
#> 2     2 cyl   6.19   1.79 -.85*                        
#> 3    3 disp 230.72 123.94 -.85*  .90*                  
#> 4      4 hp 146.69  68.56 -.78*  .83*  .79*            
#> 5    5 drat   3.60   0.53  .68* -.70* -.71* -.45*      
#> 6      6 wt   3.22   0.98 -.87*  .78*  .89*  .66* -.71*

papaja::apa_table(tab, 
                  format = "html",
                  align = c("l", rep("r", 6)))

(#tab:unnamed-chunk-3)

**

| Variables | M | SD | 1 | 2 | 3 | 4 | 5 | | :-------- | -----: | -----: | ------: | ------: | ------: | ------: | :------ | | 1 mpg | 20.09 | 6.03 | | | | | | | 2 cyl | 6.19 | 1.79 | -.85* | | | | | | 3 disp | 230.72 | 123.94 | -.85* | .90* | | | | | 4 hp | 146.69 | 68.56 | -.78* | .83* | .79* | | | | 5 drat | 3.60 | 0.53 | .68* | -.70* | -.71* | -.45* | | | 6 wt | 3.22 | 0.98 | -.87* | .78* | .89* | .66* | -.71* |

Extracting result table from structural equation model

library(lavaan)

# Estimate SEM
model.sem <- '
  # latent variables
  ind60 =~ x1 + x2 + x3
  dem60 =~ y1 + y2 + y3 + y4
  dem65 =~ y5 + y6 + y7 + y8
  # regressions
  dem60 ~ a*ind60
  dem65 ~ b*ind60 + c*dem60
  # residual covariances
  y1 ~~ y5
  y2 ~~ y4 + y6
  y3 ~~ y7
  y4 ~~ y8
  y6 ~~ y8
'
fit.sem <- sem(model.sem, 
               data = PoliticalDemocracy)

# Extracting results (only regression paths )
results <- result_table(fit.sem, 
                         sem_regressions = TRUE, 
                         new_labels = c("H1", "H2", "H3"), 
                         print = TRUE)

papaja::apa_table(results, 
                  format = "html",
                  align = c(rep("c", 3), rep("r", 6)))

(#tab:unnamed-chunk-5)

**

| outcome | predictor | label | b | se | ll | ul | p | beta | | :-----: | :-------: | :---: | ---: | ---: | ---: | ---: | ------: | ---: | | dem60 | ind60 | H1 | 1.48 | 0.40 | 0.70 | 2.27 | \< .001 | .45 | | dem65 | ind60 | H2 | 0.57 | 0.22 | 0.14 | 1.01 | .010 | .18 | | dem65 | dem60 | H3 | 0.84 | 0.10 | 0.64 | 1.03 | \< .001 | .89 |

# Print specific results for inline reporting
print_coeff(results, "H2", 
            se = FALSE, 
            beta = TRUE)
#> [1] "$b = 0.57$, 95\\% CI $[0.14, 1.01]$, $p = .010$, $\\beta = .18$"

Plotting interactions

x <- rnorm(500, 2, 1)
z <- rnorm(500, 2, 1)
y <- 0.5*x + 1.5*(z*x) + rnorm(500, 0, 3.5)
# Estimate linear model
mod.lm <- lm(y ~ x + z + x:z)
summary(mod.lm)
#> 
#> Call:
#> lm(formula = y ~ x + z + x:z)
#> 
#> Residuals:
#>     Min      1Q  Median      3Q     Max 
#> -9.4127 -2.2223 -0.0098  2.1761 11.2284 
#> 
#> Coefficients:
#>             Estimate Std. Error t value Pr(>|t|)    
#> (Intercept)   1.7221     0.7540   2.284   0.0228 *  
#> x            -0.1030     0.3510  -0.293   0.7693    
#> z            -0.5419     0.3359  -1.613   0.1074    
#> x:z           1.6292     0.1553  10.490   <2e-16 ***
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#> 
#> Residual standard error: 3.413 on 496 degrees of freedom
#> Multiple R-squared:  0.633,  Adjusted R-squared:  0.6307 
#> F-statistic: 285.1 on 3 and 496 DF,  p-value: < 2.2e-16
# Plot model
moderation_plot(mod.lm, x = "x", m = "z")

masurp/pmstats documentation built on Oct. 6, 2020, 9:24 p.m.