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Benjamin Lu; Eli Ben-Michael; Avi Feller; Luke Miratrix – Journal of Educational and Behavioral Statistics, 2023
In multisite trials, learning about treatment effect variation across sites is critical for understanding where and for whom a program works. Unadjusted comparisons, however, capture "compositional" differences in the distributions of unit-level features as well as "contextual" differences in site-level features, including…
Descriptors: Statistical Analysis, Statistical Distributions, Program Implementation, Comparative Analysis
Benjamin Lu; Eli Ben-Michael; Avi Feller; Luke Miratrix – Grantee Submission, 2022
In multisite trials, learning about treatment effect variation across sites is critical for understanding where and for whom a program works. Unadjusted comparisons, however, capture "compositional" differences in the distributions of unit-level features as well as "contextual" differences in site-level features, including…
Descriptors: Statistical Analysis, Statistical Distributions, Program Implementation, Comparative Analysis
Jance, Marsha; Thomopoulos, Nick – American Journal of Business Education, 2009
The extreme interval values and statistics (expected value, median, mode, standard deviation, and coefficient of variation) for the smallest (min) and largest (max) values of exponentially distributed variables with parameter ? = 1 are examined for different observation (sample) sizes. An extreme interval value g[subscript a] is defined as a…
Descriptors: Intervals, Statistics, Predictor Variables, Sample Size
Rosenthal, James A. – Springer, 2011
Written by a social worker for social work students, this is a nuts and bolts guide to statistics that presents complex calculations and concepts in clear, easy-to-understand language. It includes numerous examples, data sets, and issues that students will encounter in social work practice. The first section introduces basic concepts and terms to…
Descriptors: Statistics, Data Interpretation, Social Work, Social Science Research

Yoshikane, Fuyuki; Kageura, Kyo; Tsuji, Keita – Journal of the American Society for Information Science and Technology, 2003
Proposes a method for the comparative analysis of concentration in author productivity distributions; selects suitable measures, Gini's index and number of authors, for two viewpoints regarding productivity; discusses statistical peculiarities of author productivity data; and explains developmental profiles which take into account sample size…
Descriptors: Authors, Comparative Analysis, Mathematical Formulas, Measurement Techniques
Wingersky, Marilyn S.; Lord, Frederic M. – 1983
The sampling errors of maximum likelihood estimates of item-response theory parameters are studied in the case where both people and item parameters are estimated simultaneously. A check on the validity of the standard error formulas is carried out. The effect of varying sample size, test length, and the shape of the ability distribution is…
Descriptors: Error of Measurement, Estimation (Mathematics), Item Banks, Latent Trait Theory