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Adjusting for Design Effects in Disproportionate Stratified Sampling Designs Through Weighting.

This article validates the necessity of adjusting for the design effects in disproportionate stratified sampling designs through the use of sample weights. Using data from the 1958 Birth Cohort study, we demonstrate that complex sampling designs introduce sampling error and even sampling bias into s...

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Publicado en:Crime & Delinquency Vol. 60; no. 2; pp. 306 - 326
Autores principales: Tracy, Paul E., Carkin, Danielle Marie
Formato: Artículo
Publicado: Sage Publications Inc. Mar2014
Materias:
Vital records (Births, deaths, etc.)
Population research
Criminology
Proportional representation
Data analysis
Sampling errors
Parameter estimation
Acceso en línea:Ver este registro en EBSCOhost
Sumario:This article validates the necessity of adjusting for the design effects in disproportionate stratified sampling designs through the use of sample weights. Using data from the 1958 Birth Cohort study, we demonstrate that complex sampling designs introduce sampling error and even sampling bias into sample data. Such sample data are a poor representation of population parameters. These design effects can be addressed through the application of sample weights.