This function computes artifact distribution meta-analyses of d values. It supports interactive methods as well as Taylor series methods for all available corrections.
ma_d_ad(ma_obj, ad_obj_g = NULL, ad_obj_y = NULL,
correction_method = "auto", use_ic_ads = "tsa", correct_rGg = FALSE,
correct_ryy = TRUE, correct_rr_g = TRUE, correct_rr_y = TRUE,
indirect_rr_g = TRUE, indirect_rr_y = TRUE, residual_ads = TRUE,
sign_rgz = 1, sign_ryz = 1, decimals = 2, ...)Meta-analysis object of correlations or d values (regardless of input metric, output metric will be d).
Artifact-distribution object for the grouping variable (output of the link{create_ad} or link{create_ad_group} functions).
If ma_obj is of the class ma_master (i.e,. the output of ma_r or ma_d), the object supplied for
ad_obj_g must be a named list of artifact distributions with names.
corresponding to the "X" constructs in the meta-analyses contained within ma_obj.
Artifact-distribution object for the Y variable (output of the create_ad function).
If ma_obj is of the class ma_master, the object supplied for ad_obj_y must be a named list of artifact distributions with names
corresponding to the "Y" constructs in the meta-analyses contained within ma_obj.
One of the following methods for correcting artifacts: "auto", "meas", "uvdrr", "uvirr", "bvdrr", "bvirr", "rbOrig", "rb1Orig", "rb2Orig", "rbAdj", "rb1Adj", and "rb2Adj". (note: "rb1Orig", "rb2Orig", "rb1Adj", and "rb2Adj" can only be used when Taylor series artifact distributions are provided and "rbOrig" and "rbAdj" can only be used when interative artifact distributions are provided). See "Details" for descriptions of the available methods.
Determines whether artifact distributions should be extracted from the individual correction results in ma_obj.
Only evaluated when ad_obj_g or ad_obj_y is NULL and ma_obj does not contain individual correction results.
Use one of the following commands: tsa to use the Taylor series method or int to use the interactive method.
Logical argument that determines whether to correct the grouping variable for measurement error (TRUE) or not (FALSE).
Logical argument that determines whether to correct the Y variable for measurement error (TRUE) or not (FALSE).
Logical argument that determines whether to correct the grouping variable for range restriction (TRUE) or not (FALSE).
Logical argument that determines whether to correct the Y variable for range restriction (TRUE) or not (FALSE).
If correct_rr_g = TRUE: Logical argument that determines whether to correct for indirect range restriction in the grouping variable (TRUE) or not (FALSE).
If correct_rr_y = TRUE: Logical argument that determines whether to correct for indirect range restriction in Y (TRUE) or not (FALSE).
Logical argument that determines whether to use residualized variances (TRUE) or observed variances (FALSE) of artifact distributions to estimate sd_delta.
Sign of the relationship between the grouping variable and the selection mechanism (for use with the bvirr correction_method only).
Sign of the relationship between Y and the selection mechanism (for use with the bvirr correction_method only).
Number of decimal places to which interactive artifact distributions should be rounded (default is 2 decimal places). Rounding artifact distributions can help to consolidate trivially different values and speed up the computation of meta-analyses (especially in simulations).
Additional arguments.
A list object of the classes psychmeta, ma_r_as_d or ma_d_as_d, ma_bb, and ma_ad (and that inherits class ma_ic from ma_obj)
The options for correction_method are:
"auto" Automatic selection of the most appropriate correction procedure, based on the available artifacts and the logical arguments provided to the function. (default)
"meas" Correction for measurement error only.
"uvdrr" Correction for univariate direct range restriction (i.e., Case II). The choice of which variable to correct for range restriction is made using the correct_rr_x and correct_rr_y arguments.
"uvirr" Correction for univariate indirect range restriction (i.e., Case IV). The choice of which variable to correct for range restriction is made using the correct_rr_x and correct_rr_y arguments.
"bvdrr" Correction for bivariate direct range restriction. Use with caution: This correction is an approximation only and is known to have a positive bias.
"bvirr" Correction for bivariate indirect range restriction (i.e., Case V).
"rbOrig" Not recommended: Raju and Burke's version of the correction for direct range restriction, applied interactively. We recommend using "uvdrr" instead.
"rbAdj" Not recommended: Raju and Burke's version of the correction for direct range restriction, applied interactively. Adjusted to account for range restriction in the reliability of the Y variable. We recommend using "uvdrr" instead.
"rb1Orig" Not recommended: Raju and Burke's version of the correction for direct range restriction, applied using their TSA1 method. We recommend using "uvdrr" instead.
"rb1Adj" Not recommended: Raju and Burke's version of the correction for direct range restriction, applied using their TSA1 method. Adjusted to account for range restriction in the reliability of the Y variable. We recommend using "uvdrr" instead.
"rb2Orig" Not recommended: Raju and Burke's version of the correction for direct range restriction, applied using their TSA2 method. We recommend using "uvdrr" instead.
"rb2Adj" Not recommended: Raju and Burke's version of the correction for direct range restriction, applied using their TSA2 method. Adjusted to account for range restriction in the reliability of the Y variable. We recommend using "uvdrr" instead.
Schmidt, F. L., & Hunter, J. E. (2015). Methods of meta-analysis: Correcting error and bias in research findings (3rd ed.). Thousand Oaks, California: SAGE Publications, Inc. Chapter 4.
Law, K. S., Schmidt, F. L., & Hunter, J. E. (1994). Nonlinearity of range corrections in meta-analysis: Test of an improved procedure. Journal of Applied Psychology, 79(3), 425.
Dahlke, J. A., & Wiernik, B. M. (2017). One of these artifacts is not like the others: New methods to account for the unique implications of indirect range-restriction corrections in organizational research. Unpublished manuscript.
Raju, N. S., & Burke, M. J. (1983). Two new procedures for studying validity generalization. Journal of Applied Psychology, 68(3), 382. https://doi.org/10.1037/0021-9010.68.3.382