A procedure for determining the optimal number of conditions to use in multifaceted measurement designs when resource constraints are imposed is presented. The procedure is illustrated for the case in which the costs per condition vary within the same facet.
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References
1.
Choi, S. K. , & Loyd, B. H. (1988, April). An analysis of sources of variance in an observational system. Paper presented at the annual meeting of the American Educational Research Association, New Orleans, LA.
2.
Erlich, O. , & Shavelson, R. J. (1976). The search for correlations between measures of teacher behavior and student achievement: Measurement problem, conceptualization problem or both?Journal of Educational Measurement, 15, 77-89.
3.
Marcoulides, G. A. (1993). Maximizing power in generalizability studies under budget constraints. Journal of Educational Statistics, 18(2), 197-206.
4.
Marcoulides, G. A. (1994). Selecting weighting schemes in multivariate generalizability studies. Educational and Psychological Measurement, 54(1), 3-7.
5.
Marcoulides, G. A. , & Goldstein, Z. (1990). The optimization of generalizability studies with resource constraints. Educational and Psychological Measurement, 50, 761-768.
6.
Marcoulides, G. A. , & Goldstein, Z. (1991). Selecting the number of observations in multivariate measurement studies under budget constraints. Educational and Psychological Measurement, 51, 573-584.
7.
Webb, N. M. , Shavelson, R. J., Kim, K., & Chen, Z. (1989). Reliability (generalizability) of job performance measurements: Navy machinist mates. Military Psychology, 1(2), 91-110.
