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Selecting a Sample for Your Experiment: A Non-Random Stratified Sampling Approach

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Title: Selecting a Sample for Your Experiment: A Non-Random Stratified Sampling Approach
Language: English
Authors: Tipton, Elizabeth, Society for Research on Educational Effectiveness (SREE)
Source: Society for Research on Educational Effectiveness. 2012.
Availability: Society for Research on Educational Effectiveness. 2040 Sheridan Road, Evanston, IL 60208. Tel: 202-495-0920; Fax: 202-640-4401; e-mail: inquiries@sree.org; Web site: http://www.sree.org
Peer Reviewed: N
Physical Description: PDF
Page Count: 6
Publication Date: 2012
Document Type: Reports - Descriptive
Descriptors: Sampling, Experiments, Statistical Studies, Generalization
Abstract: The purpose of this paper is to develop a more general method for sample recruitment in experiments that is purposive (not random) and that results in a sample that is compositionally similar to the generalization population. This work builds on Tipton et al. (2011) by offering solutions to a larger class of problems than the non-overlapping eligible and population case described in this paper. There are three parts to this approach: (1) Populations and samples defined; (2) Covariate selection assumptions; and (3) Sample selection method.
Abstractor: ERIC
Number of References: 10
Entry Date: 2012
Accession Number: ED530563
Database: ERIC
FullText Text:
  Availability: 0
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  Data: Society for Research on Educational Effectiveness. 2040 Sheridan Road, Evanston, IL 60208. Tel: 202-495-0920; Fax: 202-640-4401; e-mail: inquiries@sree.org; Web site: http://www.sree.org
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  Data: The purpose of this paper is to develop a more general method for sample recruitment in experiments that is purposive (not random) and that results in a sample that is compositionally similar to the generalization population. This work builds on Tipton et al. (2011) by offering solutions to a larger class of problems than the non-overlapping eligible and population case described in this paper. There are three parts to this approach: (1) Populations and samples defined; (2) Covariate selection assumptions; and (3) Sample selection method.
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