Análisis No Paramčtrico de Tablas Cruzadas

Contingency Tables, Cross-tabs, Chi-Square Tests... [return to Table of Contents]

(Ordinal by Ordinal, 5-by-5 table or less) http://statpages.org/ordinal.html

• Chi-Square tests...
  • 2-by-2 table analysis (Chi-square, Fisher Exact Test, sensitivity, odds ratio, relative risk, difference in proportions, number needed to treat, etc.) with confidence intervals. Also see Andrew Mackinnon's DAG_Stat  -- an Excel spreadsheet that contains even more quantities (with confidence intervals) that can be derived from a 2x2 table).
  • EpiMax Table Calculator -- similar to the above, but with a clearer screen layout.
  • for 2-by-2 table, by Fisher Exact, and by Chi Square (with and without Yates' correction), with a good explanation
  • for 2-by-2 table
  • 2-by-2 table analysis (Chi Square, Fisher Exact, difference in proportions, risk ratio, odds ratio, theta, log-odds ratio, Poisson test)
  • for 2-by-N table, where the two rows represent dichotomies like lived/died, present/absent, yes/no. This can test for a trend in the probability of an event when you have counts of the two categories over a set of time intervals.
  • for table up to about 30 cells
  • Chi-square Test for Relationship -- for up to a 6-by-6 cross-tab.
  • for up to 10-by-10 tables. This page also has a section for comparing observed with explicitly-specified frequencies.
  • for any-size table
  • another for any-size table
  • another for any-size table (When you get to the Rweb page, scroll down to the Analysis Menu and select Two Way.)
  • Exhaustive analysis of 2-by-2 tables, with Pearson Chi-square, Likelyhood Ratio Chi-Square, Yates Chi-square, Mantel Haenszel Chi-square, Odds Ratio, Log Odds Ratio, Yules-Q, Yules-Y, Phi-square, Pearson correlation, and McNemar Test
  • Paired Proportion Test -- for testing whether the proportion of subjects having some characteristic is the same in two matched groups or in one group before and after some intervention. (Also can test against a null hypothesis specifying some non-zero difference.)
  • Also see the Evidence-Based-Medicine (EBM) calculator in the "Biostatistical Calculators" section of the "Other Statistical Tests and Analyses" section of this page.
• Three-dimensional Tables (2x2x2)...
  • Three-dimensional 2x2x2 table
  • Log-Linear Analysis for a 2x2x2 Table of Cross-Categorized Frequency Data [Calculates the values of G2 for first- and second-order interaction effects for a table of observed frequency data cross-classified according to three categorical variables, A, B, and C, each of which has two levels or subcategories (a1, a2; b1, b2; c1, c2)]
• Fisher Exact tests for contingency tables...
  • Fisher exact (2x2)
  • Fisher exact (2x2)
  • Fisher exact (2x2)
  • Fisher Exact, with good Help discussion
  • Fisher Exact (2x5)
• Exact unconditional homogeneity/independence tests for 2-by-2 tables
  (said to be more powerful than the Fisher exact test!)
• Test differences between two observed proportions, based on the Binomial distribution
• Contingency table for sequenced categories (Ordinal by Ordinal, 5-by-5 table or less)
• Contingency table for sequenced categories, 5-by-2 table, with exact probability calculations
• Spearman's correlation from cross-tabbed data with sequenced row and column categories
• McNemar's test to analyze a matched case-control study, with a good explanation
• McNemar's test for paired contingency tables
• Exact Bayes test for independence in r by c contingency tables -- Can also handle comparison of observed-vs-expected, and observed-vs-uniform situations.
• Comparison of ratings or rankings by different raters...
  • Friedman test for comparing rankings (Ordinal by Nominal)
  • Quantify agreement with kappa -- assesses how well two observers, or two methods, classify subjects into groups. For up to a 12-by-12 table.
  • Cohen's Kappa for comparing the way two raters scored each of a number of items, using case-by-case data entry
  • Another Cohen's Kappa, for case-by-case data
  • Another Cohen's Kappa, using already-tabulated data
  • Kappa for nominal data as concordance between multiple raters -- Each of several raters puts each of several entities into one of several categories
  • Intraclass correlation for concordance between multiple raters, using a data matrix that tells how each rater scored each case
• Chi-Square test for equality of distributions
• Chi-Square "Goodness of Fit" test for observed vs expected counts (NOT from Contingency Tables)...
  • Chi Square test -- takes observed values, and expected values that can be specified as expected occurrences, or percentages or fractions of the total. Data can be typed in or copied and pasted.
  • Chi-Square test
  • Chi-Square test
  • Chi-Square test (for up to 8 categories)
  • Chi-Square test for up to 10 categories. This page also has a section for up to a 10-by-10 contingency table