A General Statistical Framework for Adjustment of Rates

Datos Bibliográficos

ID2331665
AutoresClifford C Clogg (Pennsylvania State University), James W Shockey (0000-0003-0138-5451, University of Arizona), Scott R Eliason (University of Iowa)
Año1990
Volumen19
Número2
Páginas156-195
Fecha de publicación1990-11-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaSociological Methods & Research (JOURNAL)
Identificadores de la revistaISSN: 0049-1241 • E-ISSN: 1552-8294
EditorialSAGE Publications Inc (PUBLISHER)
DOI10.1177/0049124190019002002
OpenAlexW2018057258
IdiomaEN
Citas recibidas16
Referencias citadas39

A general framework is presented that integrates standardization procedures common in demography, biometrics, and other areas with statistical methodology for the analysis of log-linear models. A family of rate-adjustment methods is derived from the log-linear model; the conventional method of direct standardization is a special case. Extensions of earlier methods include (a) adjustment for three-factor interaction, (b) adjustment for marginal association between composition and group, (c) adjustments that use a standard group, and (d) adjustments that control for both marginal composition-group interaction and three-factor interaction. Statistical inference for adjusted rates is facilitated in several ways: (a) by presenting key hypotheses that can be tested routinely with log-linear methods, (b) by efficient point and interval estimation of rates, (c) by assessing the sampling variability of absolute or relative comparisons of rates across groups, and (d) by smoothing the data. Examples illustrate the flexibility of the proposed framework

Biometrics · Econometrics · Flexibility (engineering) · Inference · Point estimation · Smoothing · Standard error · Standardization · Statistical inference · Statistical model · Statistics · Artificial Intelligence · Bayesian Methods and Mixture Models · Computer Science · Mathematics · Statistical Methods and Bayesian Inference · Statistical Methods and Inference