Delve is committed to training and teaching. This commitment extends beyond psychotherapy. Because we have professionals with research and statistics training and experience, we have the opportunity to share some resources with others who may benefit!

On this page, we share several worksheets, excel calculators, code snippets, and links to documents that may help students in their research endeavors. If you spot any mistakes, please let me know directly at adam@delvepsych.com. I am not the author of all of these documents, but I did author many of them.

We also include an hours tracking excel spreadsheet for doctoral level psychology students authored by Dr. Bink. This worksheet aligns nearly perfectly with the APPIC application (APPI).

Hours Tracking (Internship)

Writing

• Using Google Scholar (Info videos; sorry for the loud music)

General tools, calculators, how-tos

Links

Calculate confidence interval for indirect effects
Calculation for the Sobel Test

Multiple Imputation using Stochastic Regression

You will need to install the ‘mice’ package.

Example code:

library(mice)
data1 = read.csv('[filepath]')
tempdata = mice(data = data1,m=5, maxit=5,seed=500, methods='mice.impute.pmm')
completedData <- complete(tempdata,5)

write.csv(completedData, file = '[destinationfilepath]')

Citations supporting this approach

R Package Documentation

Buuren, S. V., & Groothuis-Oudshoorn, K. (2010). mice: Multivariate imputation by chained equations in R. Journal of statistical software, 1-68.

Brockmeier, L. L., Kromrey, J. D., & Hines, C. V. (1998). Systematically missing data and multiple regression analysis: an empirical comparison of deletion and imputation techniques. Multiple Linear Regression Viewpoints, 25, 20-39.

Dealing with Alpha-Inflation

Structural Equation Modeling

Meta-Analyses

A macro for calculating d, v, w, and Meanes

*' ---------------------------------------------------------------------------------------------------------------------------------------------------
*' Adjust D based on small sample sizes. ES refers to raw sample sizes. D refers to edjusted sample sizes. 
*' ---------------------------------------------------------------------------------------------------------------------------------------------------

COMPUTE D = ES* (1- (3/ ( (4* (NT+NC) ) -9 ) ) ) .
COMPUTE V = ( (NT+NC) / (NT*NC) ) + ( (D**2) / (2* (NT+NC) ) ) .
COMPUTE w = 1/V .
EXECUTE .

*' ---------------------------------------------------------------------------------------------------------------------------------------------------
*' Run the Meanes macro below based on D and W (Don't use ES).
*' ---------------------------------------------------------------------------------------------------------------------------------------------------

INCLUDE "C:\Users\Main\Documents\Stats\MEANES.SPS" .
MEANES ES= D /W= W /PRINT=c .
*' E.g., MEANES ES = D /W = IVWEIGHT .

*' ---------------------------------------------------------------------------------------------------------------------------------------------------
*' If Homogenity test is significant, use the random variance component to adjust V and W using the syntax below
*' ---------------------------------------------------------------------------------------------------------------------------------------------------

COMPUTE VAdjusted = V+0.224 .
EXECUTE .

COMPUTE wadjusted = 1/VAdjusted .
EXECUTE .

*' ---------------------------------------------------------------------------------------------------------------------------------------------------
*' Rerun the Meanes macro using D and wadjusted
*' ---------------------------------------------------------------------------------------------------------------------------------------------------

INCLUDE "C:\Users\Main\Documents\Stats\MEANES.SPS" .
MEANES ES= D /W= wadjusted /PRINT=c .
*' E.g., MEANES ES = D /W = IVWEIGHT .

Sample size analysis for mediation models

I think these have generally be accepted for mediation models

• Schoemann, A. M., Boulton, A. J., & Short, S. D. (2017). Determining power and sample size for simple and complex mediation models. Social Psychological and Personality Science, 8(4), 379-386.

• https://schoemanna.shinyapps.io/mc_power_med/

• https://www.afhayes.com/introduction-to-mediation-moderation-and-conditional-process-analysis.html

Process Macro

• https://www.processmacro.org/index.html
• Code Resources from AF HAYES