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OptinMon 25 - Effect Size Statistics

Effect Size Statistics: How to Calculate the Odds Ratio from a Chi-Square Cross-tabulation Table

by Karen Grace-Martin Leave a Comment

Lest you believe that odds ratios are merely the domain of logistic regression, I’m here to tell you it’s not true.

One of the simplest ways to calculate an odds ratio is from a cross tabulation table.

We usually analyze these tables with a categorical statistical test. There are a few options, depending on the sample size and the design, but common ones are Chi-Square test of independence or homogeneity, or a Fisher’s exact test.

[Read more…] about Effect Size Statistics: How to Calculate the Odds Ratio from a Chi-Square Cross-tabulation Table

Tagged With: chi-square test, Crosstabulation, effect size statistics, odds ratio, probability

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  • Logistic Regression Analysis: Understanding Odds and Probability
  • Odds Ratio: Standardized or Unstandardized Effect Size?
  • What is a Chi-Square Test?
  • Chi-Square Test of Independence Rule of Thumb: n > 5

How Does the Distribution of a Population Impact the Confidence Interval?

by Jeff Meyer Leave a Comment

Spoiler alert, real data are seldom normally distributed.

How does the distribution influence the estimate of the population mean and the resulting confidence interval?

To figure this out, we randomly draw 100 observations 100 times from three distinct populations and plot the mean and corresponding 95% confidence interval of each sample.
[Read more…] about How Does the Distribution of a Population Impact the Confidence Interval?

Tagged With: confidence interval, Estimated marginal Means, normal distribution, population, right skewed, sample, sample size, shape of distribution, standard deviation, Uniform distribution

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  • How Confident Are You About Confidence Intervals?
  • How to Interpret the Width of a Confidence Interval
  • Member Training: Statistical Rules of Thumb: Essential Practices or Urban Myths?
  • 5 Ways to Increase Power in a Study

The Difference Between Association and Correlation

by Karen Grace-Martin 1 Comment

What does it mean for two variables to be correlated?

Is that the same or different than if they’re associated or related?

This is the kind of question that can feel silly, but shouldn’t. It’s just a reflection of the confusing terminology used in statistics. In this case, the technical statistical term looks like, but is not exactly the same as, the way we mean it in everyday English. [Read more…] about The Difference Between Association and Correlation

Tagged With: association, Bivariate Statistics, Correlation, Cramer's V, Kendall's tau-b, point-biserial, Polychoric correlations, rank-biserial, Somer's D, Spearman correlation, Stuart's tau-c, tetrachoric

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  • Member Training: Confusing Statistical Terms
  • How to Interpret the Width of a Confidence Interval
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  • Effect Size Statistics: How to Calculate the Odds Ratio from a Chi-Square Cross-tabulation Table

How Confident Are You About Confidence Intervals?

by Jeff Meyer 2 Comments

The results of any statistical analysis should include the confidence intervals for estimated parameters.

How confident are you that you can explain what they mean? Even those of us who have a solid understand of confidence intervals can get tripped up by the wording.

Let’s look at an example. [Read more…] about How Confident Are You About Confidence Intervals?

Tagged With: confidence interval, estimate sample sizes, sample size

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  • How Does the Distribution of a Population Impact the Confidence Interval?
  • How to Interpret the Width of a Confidence Interval
  • Member Training: Statistical Rules of Thumb: Essential Practices or Urban Myths?
  • The Effect Size: The Most Difficult Step in Calculating Sample Size Estimates

How to Interpret the Width of a Confidence Interval

by Christos Giannoulis 2 Comments

One issue with using tests of significance is that black and white cut-off points such as 5 percent or 1 percent may be difficult to justify.

Significance tests on their own do not provide much light about the nature or magnitude of any effect to which they apply.

One way of shedding more light on those issues is to use confidence intervals. Confidence intervals can be used in univariate, bivariate and multivariate analyses and meta-analytic studies.

[Read more…] about How to Interpret the Width of a Confidence Interval

Tagged With: Bivariate Statistics, confidence interval, multivariate analysis, sample size, standard error, Univariate statistics

Related Posts

  • How Does the Distribution of a Population Impact the Confidence Interval?
  • How Confident Are You About Confidence Intervals?
  • The Difference Between Association and Correlation
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Sample Size Estimation Without Past Reliable Pilot Data or Evidence

by Karen Grace-Martin 1 Comment

Here’s a common situation.

Your grant application or committee requires sample size estimates.  It’s not the calculations that are hard (though they can be), it’s getting the information to fill into the calculations.

Every article you read on it says you need to either use pilot data or another similar study as a basis for the values to enter into the software.

You have neither.

No similar studies have ever used the scale you’re using for the dependent variable.

And while you’d love to run a pilot study, it’s just not possible.  There are too many practical constraints — time, money, distance, ethics.

What do you do?

[Read more…] about Sample Size Estimation Without Past Reliable Pilot Data or Evidence

Tagged With: effect size, Power Analysis, sample size estimates, standardized effect size

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  • The Effect Size: The Most Difficult Step in Calculating Sample Size Estimates

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