Power and Sample Size David M. Thompson, Ph.D., P.T.

Slides:

Advertisements

Similar presentations

C82MST Statistical Methods 2 - Lecture 5 1 Overview of Lecture Testing the Null Hypothesis Statistical Power On What Does Power Depend? Measures of Effect.

Advertisements

Power of a test. power The power of a test (against a specific alternative value) Is a tests ability to detect a false hypothesis Is the probability that.

There are two statistical tests for mean: 1) z test – Used for large samples (n ≥ 30) 1) t test – Used for small samples (n < 30)

Parametric hypotheses tests

Hypothesis Testing making decisions using sample data.

Hypothesis Testing An introduction. Big picture Use a random sample to learn something about a larger population.

Nemours Biomedical Research Statistics March 19, 2009 Tim Bunnell, Ph.D. & Jobayer Hossain, Ph.D. Nemours Bioinformatics Core Facility.

Hypothesis Testing Steps of a Statistical Significance Test. 1. Assumptions Type of data, form of population, method of sampling, sample size.

DATA ANALYSIS I MKT525. Plan of analysis What decision must be made? What are research objectives? What do you have to know to reach those objectives?

Sample size computations Petter Mostad

Basic Elements of Testing Hypothesis Dr. M. H. Rahbar Professor of Biostatistics Department of Epidemiology Director, Data Coordinating Center College.

Power and Effect Size.

Chapter 9 Hypothesis Testing 9.4 Testing a Hypothesis about a Population Proportion.

Comparing Population Parameters (Z-test, t-tests and Chi-Square test) Dr. M. H. Rahbar Professor of Biostatistics Department of Epidemiology Director,

Module 28 Sample Size Determination Reviewed 19 July 05/ Module 28 This module explores the process of estimating the sample size required for detecting.

Hypothesis Testing and T-Tests. Hypothesis Tests Related to Differences Copyright © 2009 Pearson Education, Inc. Chapter Tests of Differences One.

Hypothesis Testing – Introduction

1 © Lecture note 3 Hypothesis Testing MAKE HYPOTHESIS ©

Chapter 20: Testing Hypotheses about Proportions

Hypothesis Testing.

Jeopardy Hypothesis Testing T-test Basics T for Indep. Samples Z-scores Probability $100 $200$200 $300 $500 $400 $300 $400 $300 $400 $500 $400.

Jump to first page HYPOTHESIS TESTING The use of sample data to make a decision either to accept or to reject a statement about a parameter value or about.

Chapter 8 Introduction to Hypothesis Testing

1/2555 สมศักดิ์ ศิวดำรงพงศ์

Demystifying statistical language in clinical research reports Tuesdays with Faculty: An EBP Evening Series February 27, 2007 David M. Thompson PT

1 Power and Sample Size in Testing One Mean. 2 Type I & Type II Error Type I Error: reject the null hypothesis when it is true. The probability of a Type.

Elementary Statistical Methods André L. Souza, Ph.D. The University of Alabama Lecture 22 Statistical Power.

Chapter 8 McGrew Elements of Inferential Statistics Dave Muenkel Geog 3000.

Learning Objectives In this chapter you will learn about the t-test and its distribution t-test for related samples t-test for independent samples hypothesis.

Inferential Statistics Body of statistical computations relevant to making inferences from findings based on sample observations to some larger population.

PY 603 – Advanced Statistics II TR 12:30-1:45pm 232 Gordon Palmer Hall Jamie DeCoster.

Introduction to sample size and power calculations Afshin Ostovar Bushehr University of Medical Sciences.

Jeopardy Hypothesis Testing t-test Basics t for Indep. Samples Related Samples t— Didn’t cover— Skip for now Ancient History $100 $200$200 $300 $500 $400.

Chapter 20: Testing Hypotheses About Proportions AP Statistics.

AP Process Test of Significance for Population Proportion.

Univariate Statistics PSYC*6060 Class 2 Peter Hausdorf University of Guelph.

Tests of Significance: The Basics ESS chapter 15 © 2013 W.H. Freeman and Company.

1 1 Slide © 2008 Thomson South-Western. All Rights Reserved Chapter 12 Tests of Goodness of Fit and Independence n Goodness of Fit Test: A Multinomial.

Chapter 7 Statistical Issues in Research Planning and Evaluation.

Chapter ?? 7 Statistical Issues in Research Planning and Evaluation C H A P T E R.

Chapter 9: Hypothesis Tests for One Population Mean 9.2 Terms, Errors, and Hypotheses.

Lec. 19 – Hypothesis Testing: The Null and Types of Error.

Ex St 801 Statistical Methods Part 2 Inference about a Single Population Mean (HYP)

Chapter 4. Inference about Process Quality

Hypothesis Testing.

STAT 312 Chapter 7 - Statistical Intervals Based on a Single Sample

Hypothesis Testing II: The Two-sample Case

Statistical inference: distribution, hypothesis testing

Hypothesis Tests: One Sample

Hypothesis Testing – Introduction

MATH 2311 Section 8.2.

Chapter 9 Hypothesis Testing

Hypothesis Tests for Two Population Proportions

SAMPLE SIZE DETERMINATION

Statistical Analysis of Data

P-value Approach for Test Conclusion

Inferences on Two Samples Summary

Statistical Inference

Chapter 9: Hypothesis Tests Based on a Single Sample

Hypothesis Tests for Proportions

Recipe for any Hypothesis Test

CHAPTER 12 Inference for Proportions

CHAPTER 12 Inference for Proportions

More on Testing 500 randomly selected U.S. adults were asked the question: “Would you be willing to pay much higher taxes in order to protect the environment?”

Statistics collection, presentation, analysis and interpretation of data Descriptive collection and description of data sets to yield meaningful information.

Inference as Decision Section 10.4.

Statistical Test A test of significance is a formal procedure for comparing observed data with a claim (also called a hypothesis) whose truth we want to.

Statistical Power.

Statistical Power And Sample Size Calculations

Presentation transcript:

Power and Sample Size David M. Thompson, Ph.D., P.T. Associate Professor Dept. of Biostatistics and Epidemiology College of Public Health, OUHSC

Power and sample size calculations EFFECT SIZE Specify or estimate any two to calculate the third.

Power The probability of rejecting the null hypothesis when a specified alternative is true. Both null and alternative hypotheses must be specified; the alternate hypothesis specifies a clinically meaningful effect size.

Sample Size To calculate sample size, first must specify:  Power = (1-) Effect size Difference in means Difference in proportions

Effect size Meaningful and detectable difference in group means, proportions, etc. … …including estimate of within group variability

In study planning: Power is customarily prespecified at .8 or .9 A minimal clinically important difference focuses the decision on the effect size, from which we calculate sample size. If practical conditions constrain the sample size, we specify that, then calculate the effect size we have prespecified power to detect with that sample.

Do it yourself resources Web primer on “hypothesis testing and statistical power” moon.ouhsc.edu/dthompso/CDM/power/hypoth.htm Java applets that explore influences of sample and effect sizes on power http://www.stat.uiowa.edu/~rlenth/Power/ Power and sample size programs (UCSF) http://www.biostat.ucsf.edu/sampsize.html