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10.1177/0146621617692079 http://scihub22266oqcxt.onion/10.1177/0146621617692079 C5978675!5978675!29882543     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Appl+Psychol+Meas 2017 ; 41 (5): 372-87 Nephropedia Template TP {{tp|p=29882543|t=2017. Plausible-Value Imputation Statistics for Detecting Item Misfit |pdf=|usr=}}{{29882543}} gab.com Text Plausible-Value Imputation Statistics for Detecting Item Misfit JO: Appl Psychol Meas http://www.kidney.de/pget.php?&tw=1&pmid=29882543 #FOAvip When tests consist of a small number of items, the use of latent trait estimates for secondary analyses is problematic. One area in particular where latent trait estimates have been problematic is when testing for item misfit. This article explores the use of plausible-value imputations to lessen the severity of the inherent measurement unreliability in shorter tests, and proposes a parametric bootstrap procedure to generate empirical sampling characteristics for null-hypothesis tests of item fit. Simulation results suggest that the proposed item-fit statistics provide conservative to nominal error detection rates. Power to detect item misfit tended to be less than Stone?s ?2* item-fit statistic but higher than the S?X2 statistic proposed by Orlando and Thissen, especially in tests with 20 or more dichotomously scored items. Twit Text FOAVip Plausible-Value Imputation Statistics for Detecting Item Misfit ????Appl Psychol Meas http://www.kidney.de/pget.php?&tw=1&pmid=29882543 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=29882543 #FOAvip English Wikipedia <ref>{{Cite pmid|29882543}}</ref> Plausible-Value Imputation Statistics for Detecting Item Misfit #MMPMID29882543 Chalmers RP; Ng V Appl Psychol Meas 2017[Jul]; 41 (5): 372-87 PMID29882543show ga When tests consist of a small number of items, the use of latent trait estimates for secondary analyses is problematic. One area in particular where latent trait estimates have been problematic is when testing for item misfit. This article explores the use of plausible-value imputations to lessen the severity of the inherent measurement unreliability in shorter tests, and proposes a parametric bootstrap procedure to generate empirical sampling characteristics for null-hypothesis tests of item fit. Simulation results suggest that the proposed item-fit statistics provide conservative to nominal error detection rates. Power to detect item misfit tended to be less than Stone?s ?2* item-fit statistic but higher than the S?X2 statistic proposed by Orlando and Thissen, especially in tests with 20 or more dichotomously scored items. äPlausible-Value Imputation Statistics for Detecting Item Misfit (epmc).pdf DeepDyve Pubget Overpricing