qcv: Quantifying Construct Validity
In qcv: Quantifying Construct Validity

Description Usage Arguments Details Value References Examples

View source: R/qcv.R

Computes key indices related to the Quantifyting Construct Validity (QCV) procedure (Westen & Rosenthal, 2003; see also Furr & Heuckeroth, in prep.)

1	qcv(n, actr, predr, medr)

`n`	sample size
`actr`	vector of actual validity correlations
`predr`	vector of predicted validity correlations (in same order as actr)
`medr`	median intercorrelation among criterion variables

This function applies procedures outlined by Westen and Rosenthal (2003; see also Furr & Heuckeroth, in prep).

Important: When entering values for the "actr" and "predr" arguments, order them identically. For example, if the "actr" values are ordered in terms of c(criterion A, criterion B, criterion C), then the values in "predr" should be placed in that same order. Otherwise all results will be incorrect.

Note that extreme zcontrast values (e.g., z > 38) create problems. The rcontrast-CV effect size is computed by converting z to p to t to r (see Westen & Rosenthal, Appendix A & B). However, R (and most other packages) doesn't have precision to convert an extremely large z (e.g., Z = 38) to a p value. For such z values, the p is converted to exactly zero. This makes it impossible to obtain t and rcontrast values. The qcv() function handles this by: a) identifying cases where p is initially exactly zero, and b) re-setting p to the smallest value possible, given the machine on which R us running (usually 2.225074e-308). It then proceeds to compute a t and rcontrast from that adjusted p value. It also prints a note stating that the adjustment has been made and that the p, t, and rcontrast values are lower-bound approximations.

ralerting-CV: The ralerting-CV effect size
rcontrast-CV: The rcontrast-CV effect size
zcontrast: The zcontrast value
p: p values associated with Zcontrast
N: Sample size
k: Number of criterion variables
szr: Standard deviation of (z-transformed) actual correlations
medr: Median intercorrelation between the critertion variables
rbarsq: Mean of the squared actual correlations (between focal test and criterion variables)
t: t-value associated with p value
rem: "Remarkablness" of size of contrast

Additional values are returned in a list, but not printed

Westen, D., & Rosenthal, R. (2003). Quantifying construct validity: Two simple measures. Journal of Personality and Social Psychology, 84, 608-618.

Furr, R. M., & Heukeroth, S. (In prep).Advancing the Interpretation and Computation of the "Quantifying Construct Validity" Procedure

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actrIM  <- c(.46, .13, -.24, -.03, .12, .03, .39, .06, .51, .08, .24, .66)
predrIM <- c(.58, .24, -.04, .06, -.04, .18, .36, .08, .64, .56, .36, .56)
qcv(n=90, actr=actrIM, predr=predrIM, medr=.075)