AssumpSure 1.1.1
Bug fixes
- Fixed detection of numeric-coded categorical variables (e.g., groups
coded as 1, 2, 3).
- Fixed incorrect detection of numeric-coded categorical variables in
Poisson, negative binomial, and zero-inflated negative binomial
models.
- Improved handling of categorical variables to accept up to 10
levels.
- Corrected error notifications to more clearly distinguish between
numeric value columns and categorical group columns.
- Corrected the interpretation of the Shapiro–Wilk test to make it
clearer.
New features and user
guidance
- Added a clear message explaining that the “categorical” are limited
to 10 levels to ensure ANOVA and Kruskal–Wallis results remain reliable
and interpretable.
- Added a clear message explaining that the “categorical” are limited
to 15 unique levels to improve validity and interpretability of Fisher’s
exact and Chi-square tests.
- Added asterisks to the boxplots and a tooltip explaining their
interpretation.
AssumpSure 1.1.0
Bug fixes
- Fixed incorrect statistical test recommendations in some cases.
- Logical columns are now detected correctly.
- Fixed a bug where continuous variables were sometimes not
recognized, which blocked parametric and nonparametric tests.
- Prevented Chi-square tests when any categorical variable has only
one level, with a clear user message.
- Correlation heatmap now accepts the prevalence filter input
- Corrected handling of covariates with perfect separation or
near-zero variance, with informative messages and robust plotting.
- Fixed intermittent failures of the bicor correlation method.
New features and user
guidance
- Added a clear message explaining that the “continuous” type does not
accept count data. Only truly continuous variables are allowed.
- Added guidance for normality testing with small sample sizes.
- Reformatted test outputs to be easier to copy into
spreadsheets.
- Added tooltips on how to interpret QQ plots and histograms.
- Improved test selection: if variances are unequal but normality
holds, recommend Welch’s tests instead of Mann–Whitney or Kruskal–Wallis
or One-Way ANOVA, depending on design.
- Added effect size estimates for t-tests, Mann-Whitney, Wilcoxon rank
sum, one-way ANOVA, and Kruskal Wallis.
- Added guidance when bicor analysis fails.
- Added a tooltip explaining interpretation of correlation
coefficients.
- Added a Shapiro–Wilk test below the histogram for checking the
normality of the dependent variable, to help users with
interpretation.
- Added tooltips for interpreting regression model assumptions.
- Added Poisson regression with a dedicated overdispersion test and
guidance.
- Added a zero-inflation test for negative binomial regression and
guidance.
- Added zero-inflated negative binomial regression.