Biased estimators of the coefficients in the linear regression model have been the subject of considerable discussion in the recent, literature. The purpose of this paper is to provide a unified approach to the study of biased estimators in an effort to determine their relative merits. The class of estimators includes the simple and the generalized ridge estimators proposed by Hoer1 and Kennard IS], the principal component estimator with extensions such as that, proposed by hIarquardt [19] and the shrunken est.imator proposed by Stein [23]. The problem of rstimating the biasing parameters is considered ntl.d illrrstrated with two examples. Linear Ilegression Biased Estimators Ridge Regression Principal Componetr ts
Two-alternative, forced-choice tests are commonly used to assess cooperation in examinations of neurocognitive functioning. Most commercially available tests do not primarily depend on comparing the total correct responses to the number expected by guessing. Nevertheless, the tests afford an opportunity to make stronger judgments about the cooperation of test-takers when the test score is lower than the range of scores expected for guessing. Unfortunately, many researchers and clinicians make serious errors in communicating what is "guessing" and what is "worse than guessing" (or malingering). This article describes proper methods of evaluating total correct responses on a forced-choice test.
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