Literature DB >> 10379691

Estimating sample sizes for continuous, binary, and ordinal outcomes in paired comparisons: practical hints.

S A Julious1, M J Campbell, D G Altman.   

Abstract

Paired data occur in crossover trials and matched case-control studies, and it is rare to find studies reporting sample size calculations associated with these types of studies, despite recommendations from editors that sample size calculations should be justified. In this article we describe some simple formulas and strategies for calculating the number of patients that should be entered into a matched or paired study when the outcome measures are continuous, binary, or ordinal.

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Year:  1999        PMID: 10379691     DOI: 10.1081/BIP-100101174

Source DB:  PubMed          Journal:  J Biopharm Stat        ISSN: 1054-3406            Impact factor:   1.051


  12 in total

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2.  A GEE Approach to Determine Sample Size for Pre- and Post-Intervention Experiments with Dropout.

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3.  Sample size calculation for before-after experiments with partially overlapping cohorts.

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Journal:  PLoS One       Date:  2016-07-19       Impact factor: 3.240

6.  Streamlining staging of lung and colorectal cancer with whole body MRI; study protocols for two multicentre, non-randomised, single-arm, prospective diagnostic accuracy studies (Streamline C and Streamline L).

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7.  CONSORT 2010 statement: extension checklist for reporting within person randomised trials.

Authors:  Nikolaos Pandis; Bryan Chung; Roberta W Scherer; Diana Elbourne; Douglas G Altman
Journal:  BMJ       Date:  2017-06-30

8.  CONSORT 2010 statement: extension to randomised crossover trials.

Authors:  Kerry Dwan; Tianjing Li; Douglas G Altman; Diana Elbourne
Journal:  BMJ       Date:  2019-07-31

Review 9.  Sample size determinations in original research protocols for randomised clinical trials submitted to UK research ethics committees: review.

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Journal:  BMC Infect Dis       Date:  2013-10-18       Impact factor: 3.090

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