Achieving a National Sample of Nursing Homes: Balancing Probability Techniques and Practicalities. Fielding, E., Beattie, E., O'Reilly, M., McMaster, M., & Group, A. Research in gerontological nursing, SLACK Incorporated, 10, 2015.
abstract   bibtex   
Sampling design is critical to the quality of quantitative research, yet it does not always receive appropriate attention in nursing research. The current article details how balancing probability techniques with practical considerations produced a representative sample of Australian nursing homes (NHs). Budgetary, logistical, and statistical constraints were managed by excluding some NHs (e.g., those too difficult to access) from the sampling frame; a stratified, random sampling methodology yielded a final sample of 53 NHs from a population of 2,774. In testing the adequacy of representation of the study population, chi-square tests for goodness of fit generated nonsignificant results for distribution by distance from major city and type of organization. A significant result for state/territory was expected and was easily corrected for by the application of weights. The current article provides recommendations for conducting high-quality, probability-based samples and stresses the importance of testing the representativeness of achieved samples. [Res Gerontol Nurs. 20xx; x(x):xx-xx.].
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 title = {Achieving a National Sample of Nursing Homes: Balancing Probability Techniques and Practicalities},
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 notes = {LR: 20151027; CI: Copyright 2015; JID: 101392499; 2015/07/07 [received]; 2015/09/04 [accepted]; aheadofprint; SO: Res Gerontol Nurs. 2015 Oct 28:1-8. doi: 10.3928/19404921-20151019-03.},
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 abstract = {Sampling design is critical to the quality of quantitative research, yet it does not always receive appropriate attention in nursing research. The current article details how balancing probability techniques with practical considerations produced a representative sample of Australian nursing homes (NHs). Budgetary, logistical, and statistical constraints were managed by excluding some NHs (e.g., those too difficult to access) from the sampling frame; a stratified, random sampling methodology yielded a final sample of 53 NHs from a population of 2,774. In testing the adequacy of representation of the study population, chi-square tests for goodness of fit generated nonsignificant results for distribution by distance from major city and type of organization. A significant result for state/territory was expected and was easily corrected for by the application of weights. The current article provides recommendations for conducting high-quality, probability-based samples and stresses the importance of testing the representativeness of achieved samples. [Res Gerontol Nurs. 20xx; x(x):xx-xx.].},
 bibtype = {article},
 author = {Fielding, E and Beattie, E and O'Reilly, M and McMaster, M and Group, AusQoL},
 journal = {Research in gerontological nursing}
}

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