Fixed an error in the ANOVA normality check where Shapiro–Wilk
failed on groups with zero variance.
Added a user-facing message explaining that normality cannot be
tested when a group has identical values.
New features
Added concise inline messages beneath continuous-variable dropdowns
in the t-test/ANOVA and LM/LMM sections to clarify that only continuous
variables are shown.
AssumpSure 1.1.3
Bugs fixes
Fixed detection of numeric-coded grouping variables for random
effects (e.g., participant IDs coded as 1, 2, 3) in LMM input.
Added a new helper function safe_run() to handle
computation interruptions gracefully in Shiny, preventing errors when
users stop a process manually.
AssumpSure 1.1.2
Bug fixes
Corrected the name of the first category in Chi-square and Fisher
tests.
Corrected error messages for Mann–Whitney U test when fewer than 2
groups or more than 2 groups are detected.
Corrected error message for one-way ANOVA when fewer than 3 groups
are detected.
Added error messages for Kruskal–Wallis test when only 1 or 2 groups
are detected.
New features
Added model metrics matrix for LM, LMM, GLM, and zero-inflated
models showing key fit statistics (AIC, BIC, logLik, etc.).
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.