1994) tested 3 different causal models of halo rater error (general impression [GI], salient dimension [SD], and inadequate discrimination [ID] models) and found that the GI model better accounted for observed halo rating error than did the SD or ID models. They also suggested that the type of halo rater error that occurs might vary as a function of rating context. The purpose of this study was to determine whether rating contexts could be manipulated that favored the operation of each of these 3 halo-error models. Results indicated, however, that GI halo error occurred in spite of experimental conditions designed specifically to induce other forms of halo rater error. This suggests that halo rater error is a unitary phenomenon that should be defined as the influence of a rater's general impression on ratings of specific ratee qualities.
Several studies which have used correlational measures to compare levels of observed halo in ratings with true halo levels have found "negative halo error," or true halo that exceeds observed halo. The authors derived a causal model of halo error based on a widely accepted definition of halo error and, in the context of this model, formulated three hypotheses to explain findings of negative halo error. Reanalyses of data reported recently by Kozlowski and Kirsch (1987) and Murphy and Reynolds (1988) supported the hypothesis that "negative" halo error can be indicated when positive halo actually occurs along with imperfect correlational rating accuracy. It is suggested that positive halo rating error may be more pervasive a phenomenon than has recently been thought.
I n t r a c l a s s c o r r e l a t i o n c o e f f i c i e n t s (ICCs) o f t e n a r e used t o index t h e l e v e l o f i n t e r r a t e r agreement f o r j o b a n a l y s i s r a t i n g s . T y p i c a l l y , ICCs a r e c a l c u l a t e d from a oneway ANOVA design f o r each o f several r a t e d j o b c h a r a c t e r i s t i c s i n which m u l t i p l e j o b a n a l y s t s r a t e m u l t i p l e jobs. ICCs a r e h i g h e s t when between mean square (BMS) i s l a r g e r e l a t i v e t o w i t h i n mean square (WMS), b u t they can be l o w e i t h e r when (a) WMS i s l a r g e , i n which case ICCs a p p r o p r i a t e l y i n d i c a t e low i n t e r r a t e r agreement, o r (b) E M i s small, i n which case ICCs r e f l e c t t h e a t t e n u a t i n g i n f l u e n c e o f range r e s t r i c t i o n on t h e grouping f a c t o r (i.e., j o b s ) . and n e g a t i v e l y w i t h WMS components and ( b ) ICCs c o v a r i e d s i g n i f i c a n t l y and p o s i t i v e l y w i t h BMS. i n t e r r a t e r agreement because they a r e s u b s t a n t i a l l y a f f e c t e d by t h e l e v e l o f between-group variance. I n t e r p r e t a t i o n a l confounding f o r ICCs can be circumvented by ( a ) u s i n g s t a t i s t i c s Using two j o b a n a l y s i s data s e t s , we found t h a t (a) ICCs c o v a r i e d s i g n i f i c a n t l y These r e s t u l t s i n d i c a t e t h a t ICCs cannot be i n t e r p r e t e d unambiguously as i n d i c e s o f designed s p e c i f i c a l l y t o index w i thin-group f o r a t t e n u a t i o n due t o range r e s t r i c t i o n .
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.