Power And Sample Size Calculator Mac App Download

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Power And Sample Size Calculator Mac App Download Rating: 6,7/10 7880 votes
  1. Free Calculator For Mac
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Command:Sample size
Survival analysis (logrank test)

Description

Calculates the required sample size for the comparison of survival rates in two independent groups.

  • G power for sample size free download - Sample Size, G Power, Sample Size Calculator App, and many more programs.
  • So you compute power retrospectively to see if the test was powerful enough or not. This is an empty question. Of course it wasn't powerful enough - that's why the result isn't significant. Power calculations are useful for design, not analysis. (Note: These comments refer to power computed based on the observed effect size and sample size.

(Note: These comments refer to power computed based on the observed effect size and sample size. Considering a different sample size is obviously prospective in nature. Considering a different effect size might make sense, but probably what you really need to do instead is.

Required input

  • Type I error - alpha: the probability of making a Type I error (α-level, two-sided), i.e. the probability of rejecting the null hypothesis when in fact it is true.
  • Type II error - beta: the probability of making a Type II error (β-level), i.e. the probability of accepting the null hypothesis when in fact it is false.
  • Survival rate Group 1: the hypothesized survival rate in the first group.
  • Survival rate Group 2: the hypothesized survival rate in the second group.
  • Ratio of sample sizes in Group 1 / Group 2: the ratio of the sample sizes in group 1 and 2. Enter 1 for equal sample sizes in both groups. Enter 2 if the number of cases in group 1 must be double of the number of cases in group 2.

Example

You are interested in detecting a difference between survival rates of 0.6 and 0.4. You plan to have twice as many cases in the first group as in the second group.

For α-level you select 0.05 and for β-level you select 0.20 (power is 80%).

Enter the values 0.6 and 0.4 for the Survival rates in Group 1 and Group 2, and enter 2 for the Ratio of sample sizes.

Results

After you click Calculate the program displays the required sample size.

In the example 129 cases are required in Group 1 and 65 cases in Group 2, giving a total of 194 cases.

A table shows the required total sample size for different Type I and Type II Error levels.

Literature

  • Machin D, Campbell MJ, Tan SB, Tan SH (2009) Sample size tables for clinical studies. 3rd ed. Chichester: Wiley-Blackwell.

See also

Recommended book

Sample Size Tables for Clinical Studies
David Machin, Michael J. Campbell, Say-Beng Tan, Sze-Huey Tan

Buy from Amazon US - CA - UK - DE - FR - ES - IT

Sample Sizes for Clinical, Laboratory and Epidemiology Studies includes the sample size software (SSS) and formulae and numerical tables needed to design valid clinical studies. The text covers clinical as well as laboratory and epidemiology studies and contains the information needed to ensure a study will form a valid contribution to medical research.

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The authors, noted experts in the field, explain step by step and explore the wide range of considerations necessary to assist investigational teams when deriving an appropriate sample size for their when planned study. The book contains sets of sample size tables with companion explanations and clear worked out examples based on real data. In addition, the text offers bibliography and references sections that are designed to be helpful with guidance on the principles discussed. S1 stereo imager vst download.

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Abstract
Presents the practical and statistical information needed to help investigators decide how large a sample to select from a population targeted for a health study or survey. Desgned to perform a cookbook function, the book uses explanatory text and abundant tabular calculations to vastly simplify the task of determining the minimum sample size needed to obtain statistically valid results. The objective is to assist those investigators, undertaking health studies at local or district level, who lack detailed knowledge of statistical methodology. Acknowledging that the size of a sample will depend on the aims, nature, and scope of the study, the first part of the book provides a practical framework for working through the steps of sample size determination once a proposed study and its objectives have been clearly defined. In six chapters, readers are introduced to a variety of situations in which minimum sample size must be determined, including studies of population proportion, odds ratio, relative risk, and disease incidence. Each situation is first defined in terms of the information required and then illustrated by a hypothetical example of a study objective and the questions that will need to be answered in order to determine the appropriate sample size. The solution to each problem is clearly stated, together with relevant explanatory notes. The second part of the book features more than 50 pages of tables that enable the reader to determine the sample size required, under simple random sampling, in a given type of study without recourse to complicated calculations. Each of the illustrative examples featured in the first part of the book includes a reference to one of these tables, thus showing investigators how to move from the objectives and design of a study to the rapid calculation of an appropriate sample size. Examples and tables were selected as representing many of the approaches most likely to be adopted in health studies