Bloomberg School BIO 751 - Lecture 3 (51 pages)

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Lecture 3



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Lecture 3

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Lecture Notes


Pages:
51
School:
Johns Hopkins Bloomberg School of Public Health
Course:
Bio 751 - Teacher’s Corner

Unformatted text preview:

This work is licensed under a Creative Commons Attribution NonCommercial ShareAlike License Your use of this material constitutes acceptance of that license and the conditions of use of materials on this site Copyright 2009 The Johns Hopkins University and Saifuddin Ahmed All rights reserved Use of these materials permitted only in accordance with license rights granted Materials provided AS IS no representations or warranties provided User assumes all responsibility for use and all liability related thereto and must independently review all materials for accuracy and efficacy May contain materials owned by others User is responsible for obtaining permissions for use from third parties as needed Methods in Sample Surveys 140 640 3rd Quarter 2009 Sample Size and Power Estimation Saifuddin Ahmed PHD Biostatistics Department School of Hygiene and Public Health Johns Hopkins University Sample size and Power When statisticians are not making their lives producing confidence intervals and p values they are often producing power calculations Newson 2001 In planning of a sample survey a stage is always reached at which a decision must be made about the size of the sample The decision is important Too large a sample implies a waste of resources and too small a sample diminishes the utility of the results Cochran 1977 Sample size estimation Why Provides validity of the clinical trials intervention studies in fact any research study even presidential election polls Assures that the intended study will have a desired power for correctly detecting a clinically meaningful difference of the study entity under study if such a difference truly exists Sample size estimation ONLY two objectives Measure with a precision Precision analysis Assure that the difference is correctly detected Power analysis First objective measure with a precision Whenever we propose to estimate population parameters such as population mean proportion or total we need to estimate with a specified level of



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