SOCR HTML5 PowerCalculatorProject

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SOCR Project - SOCR HTML5 Statistical Power Calculator Project

Background

SOCR Power Calculator Web-app

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Project goals

The goal of this project is to redesign the SOCR Java-based Power_Analysis_for_Normal_Distribution applet using only HTML5, CSS3, AJAX/JSON, and JavaScript, and in the process introduce some useful and powerful expansions of this web-app.

Project specification

The HTML5/JavaScript implementation of the new SOCR Power Calculator Web-App es expected to lower device, software and statistical-expertise barriers for all users. The following list of designs and analysis are expected to be included in the new SOCR Power Web-app, according to the power calculations included in the provided references.

The basic classification of all power/sample analysis calculations depends on:

  • Parameters: Means, Proportions, Survival, Agreement, or Regression
  • Design/Goals: One, Two, or more groups
  • Type of analysis: Test, Confidence Interval, or Equivalence

One-sample t test

Paired t test for difference in means: Power, sample size, or effect size are computed using central and non-central t distribution.

Paired t test for equivalence of means

Power, sample size, or effect size are computed using central and non-central t distribution.

Univariate one-way repeated measures analysis of variance

One-way repeated measures contrast - Power, sample size, or effect size are computed using central and non-central F.

  • Dixon, W.J., Massey, F.J. (1983) Introduction to Statistical Analysis. McGraw-Hill. Chapter 14.
  • Overall, J.E., Doyle, S.R. (1994) Estimating Sample Sizes for Repeated Measures Designs, Controlled

Clinical Trials 15:100-123.

Univariate one-way repeated measures analysis of variance

Confidence interval for mean based on z (n large)

  • Confidence interval for difference in paired means (n large)
  • Confidence interval for repeated measures contrast
  • Dixon, W.J., Massey, F.J. (1983) Introduction to Statistical Analysis. 4th Edition. McGraw-Hill. Pages 80-85.
  • Overall, J.E., Doyle, S.R. (1994) Estimating Sample Sizes for Repeated Measures Designs, Controlled Clinical Trials 15:100-123.

Confidence interval for mean based on t (with coverage probability)

  • Confidence interval for difference in paired means (coverage probability)
  • Kupper, L.L. and Hafner, K.B. (1989) How appropriate are popular sample size formulas? The American Statistician 43:101-105.
  • Hahn GJ, Meeker WQ (1991) Statistical Intervals. A guide for practitioners. John Wiley & Sons, Inc. New York.

One group t-test that a mean equals user-specified value in finite population

  • Paired t-test of mean difference equal to zero in finite population
  • Confidence interval for mean based on z (n large) adjusted for finite population
  • Confidence interval for mean based on t (with coverage probability) finite population
  • Confidence interval for difference in paired means based on z (n large) adjusted for finite population
  • Confidence interval for difference in paired means based on t (with coverage probability) finite population
  • Cochran, G. (1977) Sampling Techniques 3rd Edition. John Wiley & Sons Inc. New York, pages 23-28.

Two-sample t-test: Equivalence of two means

  • Dixon, W.J., Massey, F.J. (1983) Introduction to Statistical Analysis. McGraw-Hill.
  • O’Brien, R.G., Muller, K.E. (1993) “Unified Power Analysis for t-tests through Multivariate Hypotheses”, in Edwards, L.K. (Ed.), Applied Analysis of Variance in Behavioral Science, Marcel Dekker, New York. Chapter 8 (pp 297-344).

Two group t-test for fold change assuming log-normal distribution

  • Diletti, E., Hauschke D., Steinijans, V.W. "Sample size determination for bioequivalence assessment by means of confidence intervals" Int. Journal of Clinical Pharmacology 29(1991) p. 7.

Two group t-test of equal fold change with fold change threshold

  • Diletti, E., Hauschke D., Steinijans, V.W. "Sample size determination for bioequivalence assessment by means of confidence intervals" Int. Journal of Clinical Pharmacology 29(1991), p. 7.

Two group Satterthwaite t-test of equal means (unequal variances)

  • Moser, B.K., Stevens, G.R., Watts, C.L. "The two-sample t test versus Satterthwaite’s approximate F test" Commun. Statist.-Theory Meth. 18(1989) pp. 3963-3975.

====Two one-sided equivalence tests (TOST) for two-group design

  • Chow, S.C, Liu, J.P. Design and Analysis of Bioavailability and Bioequivalence Studies, Marcel Dekker, Inc. (1992)
  • Schuirmann DJ (1987) A comparison of the two one-sided tests procedure and the power approach for assessing the equivalence of average bioavailability, J. Pharmacokinet Biopharm 15:657-680.
  • Phillips KE (1990) Power of the two one-sided tests procedure in bioequivalence, J. Pharmacokinet Biopharm 18:137-143.
  • Owen DB (1965) A special case of a bivariate non-central t distribution. Biometrika 52:437- 446.

Ratio of means for crossover design (original scale)

  • Hauschke D, Kieser M, Diletti E, Burke M (1999) Sample size determination for proving equivalence based on the ratio of two means for normally distributed data. Statistics in Medicine 18: 93-105.

Wilcoxon (Mann-Whitney) rank-sum test that P(X<Y) = .5 (continuous outcome)

  • Noether GE (1987) Sample size determination for some common nonparametric statistics. J. Am Stat. Assn 82:645-647.

Wilcoxon (Mann-Whitney) rank-sum test that P(X<Y) = .5 (ordered categories)

  • Kolassa J (1995) A comparison of size and power calculations for the Wilcoxon statistic for ordered categorical data. Statistics in Medicine 14: 1577-1581.

Two-group univariate repeated measures analysis of variance

  • Muller, KE, Barton CN (1989) Approximate Power for Repeated-Measures ANOVA lacking Sphericity. Journal of the American Statistical Association 84:549-555.

t-test (ANOVA) for difference of means in 2 x 2 crossover design

  • Senn, Stephen. Cross-over Trials in Clinical Research, Wiley (2002) Page 285.

Confidence interval for difference of two means (N large)

  • Confidence interval width for one-way contrast
  • Dixon, W.J., Massey, F.J. (1983) Introduction to Statistical Analysis. 4th Edition. McGraw-Hill. Pages 80-85 and 130-131.
  • Confidence interval for difference of two means (coverage probability)
  • Kupper, L.L. and Hafner, K.B. (1989) How appropriate are popular sample size formulas? The American Statistician, 43:101-105.

One-way analysis of variance

  • Single one-way contrast
  • O’Brien, R.G., Muller, K.E. (1993) “Unified Power Analysis for t-tests through Multivariate Hypotheses”, in Edwards, L.K. Appendix — 7-9, (Ed.), Applied Analysis of Variance in Behavioral Science, Marcel Dekker, New York. Pages 297-344.

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Exemplary HTML5 tools that can be employed

See also





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