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Eli Ben-Michael; Lindsay Page; Luke Keele – Grantee Submission, 2024
In a clustered observational study, a treatment is assigned to groups and all units within the group are exposed to the treatment. We develop a new method for statistical adjustment in clustered observational studies using approximate balancing weights, a generalization of inverse propensity score weights that solve a convex optimization problem…
Descriptors: Research Design, Statistical Data, Multivariate Analysis, Observation
Zsuzsa Bakk; Roberto Di Mari; Jennifer Oser; Jouni Kuha – Structural Equation Modeling: A Multidisciplinary Journal, 2022
In this article, we present a two-stage estimation approach applied to multilevel latent class analysis (LCA) with covariates. We separate the estimation of the measurement and structural model. This makes the extension of the structural model computationally efficient. We investigate the robustness against misspecifications of the proposed…
Descriptors: Multivariate Analysis, Hierarchical Linear Modeling, Computation, Measurement
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
Yan, S. Y.; James, G. – International Journal of Mathematical Education in Science & Technology, 2006
The modular exponentiation, y[equivalent to]x[superscript k](mod n) with x,y,k,n integers and n [greater than] 1; is the most fundamental operation in RSA and ElGamal public-key cryptographic systems. Thus the efficiency of RSA and ElGamal depends entirely on the efficiency of the modular exponentiation. The same situation arises also in elliptic…
Descriptors: Mathematics, Item Response Theory, Calculus, Multivariate Analysis

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