000			02153nam a22002537a 4500
003			ZW-GwMSU
005			20221104123612.0
008			221104b |||||||| |||| 00| 0 eng d
040			_aMSU _cMSU _erda
100			_aWILLIAMS, Larry J.
245			_aIdeal, nonideal, and no-marker variables: The confirmatory factor analysis (CFA) marker technique works when it matters
264			_aWashington _b American Psychological Association _c2015
336			_2rdacontent _atext _btxt
337			_2rdamedia _aunmediated _bn
338			_2rdacarrier _avolume _bnc
440			_vVolume , number ,
520			_aA persistent concern in the management and applied psychology literature is the effect of common method variance on observed relations among variables. Recent work (i.e., Richardson, Simmering, & Sturman, 2009) evaluated 3 analytical approaches to controlling for common method variance, including the confirmatory factor analysis (CFA) marker technique. Their findings indicated significant problems with this technique, especially with nonideal marker variables (those with theoretical relations with substantive variables). Based on their simulation results, Richardson et al. concluded that not correcting for method variance provides more accurate estimates than using the CFA marker technique. We reexamined the effects of using marker variables in a simulation study and found the degree of error in estimates of a substantive factor correlation was relatively small in most cases, and much smaller than error associated with making no correction. Further, in instances in which the error was large, the correlations between the marker and substantive scales were higher than that found in organizational research with marker variables. We conclude that in most practical settings, the CFA marker technique yields parameter estimates close to their true values, and the criticisms made by Richardson et al. are overstated.
650			_amarker variable
650			_acommon method variance
650			_aconfirmatory factor analysis
700			_aO'BOYLE, Ernest H.
856			_u https://doi.org/10.1037/a0038855
942			_2lcc _cJA
999			_c160073 _d160073