splithalfr: splithalfr: Split-Half Reliabilities

In splithalfr: Estimate Split-Half Reliabilities

splithalfr: Split-Half Reliabilities

Description

Estimates split-half reliabilities for scoring algorithms of cognitive tasks and questionnaires.

Getting started

We've got six short vignettes to help you get started. You can open a vignette bij running the corresponding code snippets (vignette(...)) in the R console.

• vignette("rapi_sum") Sum-score for data of the 23-item version of the Rutgers Alcohol Problem Index (\Sexpr[results=rd]{tools:::Rd_expr_doi("https://doi.org/10.15288/jsa.1989.50.30")}White & Labouvie, 1989)

• vignette("vpt_diff_of_means") Difference of mean RTs for correct responses, after removing RTs below 200 ms and above 520 ms, on Visual Probe Task data (Mogg & Bradley, 1999 <\Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/026999399379050")}>)

• vignette("aat_double_diff_of_medians") Double difference of medians for correct responses on Approach Avoidance Task data (Heuer, Rinck, & Becker, 2007 <\Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.brat.2007.08.010")}>)

• vignette("iat_dscore_ri") Improved d-score algorithm for data of an Implicit Association Task that requires a correct response in order to continue to the next trial (Greenwald, Nosek, & Banaji, 2003)

• vignette("sst_ssrti") Stop-Signal Reaction Time integration method for data of a Stop Signal Task (Logan, 1981)

• vignette("gng_dprime") D-prime for data of a Go/No Go task (Miller, 1996 <\Sexpr[results=rd]{tools:::Rd_expr_doi("10.3758/BF03205476")}>)

Splitting methods

The splithalfr supports a variety of methods for splitting your data. We review and assess each method in the compendium paper (Pronk et al., 2021 <\Sexpr[results=rd]{tools:::Rd_expr_doi("https://doi.org/10.3758/s13423-021-01948-3")}>). This vignette illustrates how to apply each splitting method via the splithalfr: vignette("splitting_methods")

• first-second and odd-even (Green et al., 2016 <\Sexpr[results=rd]{tools:::Rd_expr_doi("10.3758/s13423-015-0968-3")}>; Webb, Shavelson, & Haertel, 1996 <\Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/S0169-7161(06)26004-8")}>; Williams & Kaufmann, 2012 <\Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.jesp.2012.03.001")}>)

• stratified (Green et al., 2016 <\Sexpr[results=rd]{tools:::Rd_expr_doi("10.3758/s13423-015-0968-3")}>)

• permutated/bootstrapped/random sample of split halves (Kopp, Lange, & Steinke, 2021 <\Sexpr[results=rd]{tools:::Rd_expr_doi("10.1177/1073191119866257")}>, Parsons, Kruijt, & Fox, 2019 <\Sexpr[results=rd]{tools:::Rd_expr_doi("10.1177/2515245919879695")}>; Williams & Kaufmann, 2012 <\Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.jesp.2012.03.001")}>)

• Monte Carlo (Williams & Kaufmann, 2012 <\Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.jesp.2012.03.001")}>)

Validation of split-half estimations

Part of the splithalfr algorithm has been validated via a set of simulations that are not included in this package. The R script for these simulations can be found here.

Related packages

These R packages offer bootstrapped split-half reliabilities for specific scoring algorithms and are available via CRAN at the time of this writing: multicon, psych, and splithalf.

Acknowledgments

I would like to thank Craig Hedge, Eva Schmitz, Fadie Hanna, Helle Larsen, Marilisa Boffo, and Marjolein Zee for making datasets available for inclusion in the splithalfr. Additionally, I would like to thank Craig Hedge and Benedict Williams for sharing R-scripts with scoring algorithms that were adapted for splithalfr vignettes. Finally, I would like to thank Mae Nuijs and Sera-Maren Wiechert for spotting bugs in earlier versions of this package.

Author(s)

Maintainer: Thomas Pronk [e-mail]

See Also

Useful links:

• https://github.com/tpronk/splithalfr

• Report bugs at https://github.com/tpronk/splithalfr/issues

splithalfr documentation built on Sept. 15, 2023, 1:08 a.m.