Literature DB >> 10530651

Who is at risk of what?

D Birnbaum1.   

Abstract

If you have calculated the sample size required for an employee survey or an observational study of departmental practices but found that the number of observations required is larger than the number of employees, chances are the error is due to use of approximation formulae. Many of us unknowingly were taught to use approximations that fail to include the finite population correction factor. Depending on the objective of a study and the proportion of a population sampled, it may be necessary to consider this correction factor in order to estimate standard error and sample size accurately.

Mesh:

Year:  1999        PMID: 10530651     DOI: 10.1086/501570

Source DB:  PubMed          Journal:  Infect Control Hosp Epidemiol        ISSN: 0899-823X            Impact factor:   3.254


  3 in total

1.  Access and use of medicines information sources by physicians in public hospitals in Uganda: a cross-sectional survey.

Authors:  Winifred A Tumwikirize; Jasper W Ogwal-Okeng; Osa Vernby; Willy W Anokbonggo; Lars L Gustafsson; Cecilia S Lundborg
Journal:  Afr Health Sci       Date:  2008-12       Impact factor: 0.927

2.  Accounting for the rarity of the disease when designing clinical trials with a focus on pediatric cancers.

Authors:  Audrey Mauguen
Journal:  Clin Trials       Date:  2022-03-01       Impact factor: 2.599

3.  Inter- and intra-observer reliability of clinical movement-control tests for marines.

Authors:  Andreas Monnier; Joachim Heuer; Kjell Norman; Björn O Äng
Journal:  BMC Musculoskelet Disord       Date:  2012-12-29       Impact factor: 2.362

  3 in total

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