estimate_var_tsa | R Documentation |
Functions to estimate the variances corrected for psychometric artifacts. These functions use Taylor series approximations (i.e., the delta method) to estimate the corrected variance of an effect-size distribution.
The available Taylor-series functions include:
estimate_var_tsa_meas
: Variance of \rho
corrected for measurement error only
estimate_var_tsa_uvdrr
: Variance of \rho
corrected for univariate direct range restriction (i.e., Case II) and measurement error
estimate_var_tsa_bvdrr
: Variance of \rho
corrected for bivariate direct range restriction and measurement error
estimate_var_tsa_uvirr
: Variance of \rho
corrected for univariate indirect range restriction (i.e., Case IV) and measurement error
estimate_var_tsa_bvirr
: Variance of \rho
corrected for bivariate indirect range restriction (i.e., Case V) and measurement error
estimate_var_tsa_rb1
: Variance of \rho
corrected using Raju and Burke's TSA1 correction for direct range restriction and measurement error
estimate_var_tsa_rb2
: Variance of \rho
corrected using Raju and Burke's TSA2 correction for direct range restriction and measurement error. Note that a typographical error in Raju and Burke's article has been corrected in this function so as to compute appropriate partial derivatives.
estimate_var_tsa_meas(mean_rtp, var = 0, mean_qx = 1, mean_qy = 1, ...)
estimate_var_tsa_uvdrr(
mean_rtpa,
var = 0,
mean_ux = 1,
mean_qxa = 1,
mean_qyi = 1,
...
)
estimate_var_tsa_bvdrr(
mean_rtpa,
var = 0,
mean_ux = 1,
mean_uy = 1,
mean_qxa = 1,
mean_qya = 1,
...
)
estimate_var_tsa_uvirr(
mean_rtpa,
var = 0,
mean_ut = 1,
mean_qxa = 1,
mean_qyi = 1,
...
)
estimate_var_tsa_bvirr(
mean_rtpa,
var = 0,
mean_ux = 1,
mean_uy = 1,
mean_qxa = 1,
mean_qya = 1,
sign_rxz = 1,
sign_ryz = 1,
...
)
estimate_var_tsa_rb1(
mean_rtpa,
var = 0,
mean_ux = 1,
mean_rxx = 1,
mean_ryy = 1,
...
)
estimate_var_tsa_rb2(
mean_rtpa,
var = 0,
mean_ux = 1,
mean_qx = 1,
mean_qy = 1,
...
)
mean_rtp |
Mean corrected correlation. |
var |
Variance to be corrected for artifacts. |
mean_qx |
Mean square root of reliability for X. |
mean_qy |
Mean square root of reliability for Y. |
... |
Additional arguments. |
mean_rtpa |
Mean corrected correlation. |
mean_ux |
Mean observed-score u ratio for X. |
mean_qxa |
Mean square root of unrestricted reliability for X. |
mean_qyi |
Mean square root of restricted reliability for Y. |
mean_uy |
Mean observed-score u ratio for Y. |
mean_qya |
Mean square root of unrestricted reliability for Y. |
mean_ut |
Mean true-score u ratio for X. |
sign_rxz |
Sign of the relationship between X and the selection mechanism. |
sign_ryz |
Sign of the relationship between Y and the selection mechanism. |
mean_rxx |
Mean reliability for X. |
mean_ryy |
Mean reliability for Y. |
Vector of variances corrected for mean artifacts via Taylor series approximation.
A typographical error in Raju and Burke's article has been corrected in estimate_var_tsa_rb2()
so as to compute appropriate partial derivatives.
Dahlke, J. A., & Wiernik, B. M. (2020). Not restricted to selection research: Accounting for indirect range restriction in organizational research. Organizational Research Methods, 23(4), 717–749. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1177/1094428119859398")}
Hunter, J. E., Schmidt, F. L., & Le, H. (2006). Implications of direct and indirect range restriction for meta-analysis methods and findings. Journal of Applied Psychology, 91(3), 594–612. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1037/0021-9010.91.3.594")}
Raju, N. S., & Burke, M. J. (1983). Two new procedures for studying validity generalization. Journal of Applied Psychology, 68(3), 382–395. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1037/0021-9010.68.3.382")}
estimate_var_tsa_meas(mean_rtp = .5, var = .02,
mean_qx = .8,
mean_qy = .8)
estimate_var_tsa_uvdrr(mean_rtpa = .5, var = .02,
mean_ux = .8,
mean_qxa = .8,
mean_qyi = .8)
estimate_var_tsa_bvdrr(mean_rtpa = .5, var = .02,
mean_ux = .8,
mean_uy = .8,
mean_qxa = .8,
mean_qya = .8)
estimate_var_tsa_uvirr(mean_rtpa = .5, var = .02,
mean_ut = .8,
mean_qxa = .8,
mean_qyi = .8)
estimate_var_tsa_bvirr(mean_rtpa = .5, var = .02,
mean_ux = .8,
mean_uy = .8,
mean_qxa = .8,
mean_qya = .8,
sign_rxz = 1, sign_ryz = 1)
estimate_var_tsa_rb1(mean_rtpa = .5, var = .02,
mean_ux = .8,
mean_rxx = .8,
mean_ryy = .8)
estimate_var_tsa_rb2(mean_rtpa = .5, var = .02,
mean_ux = .8,
mean_qx = .8,
mean_qy = .8)
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