CONTENT Validity extent to which a measure represents a given construct.

CONVERGENT VALIDITY shows theoretically based similarities between measurable construct & is subcategory of construct validity/scales should have positive correlation w other measures of the same construct using PEARSON R as measure for correlation coefficients. Pearson correlation range is -1.00to +1.00. in reliability coefficients the greater the coefficient, the higher the reliability. CRONBACH’S ALPHA – MOST POPULAR reliability statistic!!! scores are .00-+1.00-alpha score is closer to one when items are correlated & measuring the same construct/DETERMINES INTERNAL CONSISTENCY & instruments overall reliability homogeneity of items. SHOULD be calculated each time a scale is use to see if remains stable over multiple studies. (a Alpha) range normally 0 and 1. IE: >.9=excellent and >.5 unacceptable. MTMM can enhance further validity/complex method use multiple methods matrix or correlations 2 interpret assessment of construct validity. INTERNAL CONSISTENCY degree of homogeneity of scale items but gets confused w homogeneity of scale/ homo – refers tone dimensional scale & interrelatedness is a term that includes both 1 dimensional & multidimensional scales. Int consistency is concerned w interrelatedness of sample test items/homogeneity refers homogeneity.TEST-RETESTmeasures temporal stability how”constant scores remain from one occasion to another”score is influenced by numerous factors such as real change construct, changes due to subject variability or unreliable measure. Individuals can influence reliability w deliberate effect/ONLY reliable measure when the phenomenon has remained stable. ALPHA COEFFICIENT .70 or greater is a good standard to estimate reliability INTER-ITEM CORRELATION used to determine which items should be removed from the scale between .20 & .80 R ideal/closer alpha is to 1, the greater the INTERNAL CONSISTENCY/if an item does not contribute to the IC of the scale – item should be excluded from the scale. EIGENVALUES- amount of variance that is accounted for by each factor in FA is referred to as the eigenvalue/helps researcher to determine factors to keep and which to discard/values less that .1 are…