ifr_cochran_qtest() now maps each factor by its own
declared level order, accepting factors with different labels and using
explicit numeric evidence to resolve the shared coding of numeric
columns.ifr_cochran_qtest() now resolves the shared numeric
0/1 or 1/2 coding before incomplete rows are
dropped, so a homogeneous numeric column of all 1s follows
numeric evidence or consistent factor-label hints, and ambiguous
mixtures error instead of being silently misread.ifr_os_prop_test() now requires the null probability to
be strictly inside (0, 1), because the normal approximation
is undefined at prob = 0 or prob = 1.ifr_runs_test() now computes its p-value from the upper
normal tail, so small representable p-values are no longer returned as
zero.ifr_os_t_test() now detects essentially constant data
relative to the mean, so a change of units no longer changes whether the
t statistic can be estimated, and numerically degenerate data are
rejected.ifr_cochran_qtest() now keeps the declared levels of a
binary factor, so a homogeneous factor column is accepted when the pairs
are discordant elsewhere.ifr_runs_test() and ifr_cochran_qtest()
now report a clear error when the number of runs has zero variance or
the data contain no within-subject discordance, instead of returning
NaN.ifr_mcnemar_test() now computes both chi-square
p-values from the upper tail, so small representable p-values are no
longer returned as zero.ifr_ts_prop_group() now defines one success level
before tabulating the groups, so character, logical and 0/1 outcomes
work when a group contains only successes or only failures.ifr_binom_calc(), ifr_binom_test(),
ifr_os_prop_test(), ifr_os_t_test(),
ifr_runs_test() and ifr_cochran_qtest() now
reject invalid counts, probabilities, sample sizes and degenerate
samples instead of returning plausible-looking values. The runs and
Cochran tests remove incomplete observations with a documented,
consistent policy.ifr_cochran_qtest() now computes its p-value from the
upper tail, so small representable p-values are no longer returned as
zero.ifr_ts_ind_ttest() now drops unused grouping levels
after removing incomplete cases, so a factor that declares a third level
does not reject data with two observed groups.ifr_os_prop_test() and
ifr_chisq_assoc_test() now compute p-values from unrounded
z and chi-square statistics, so the reported decimals match the
statistical reference.ifr_os_var_test() now reports the correct confidence
interval for the standard deviation.ifr_ts_ind_ttest() now uses t quantiles, rather than
normal quantiles, for the confidence interval of the mean difference and
reports both the pooled and Satterthwaite intervals.ifr_cochran_qtest() now recodes logical, 0/1, 1/2 and
two-level factor columns to 0/1, and rejects other inputs.ifr_oneway_anova() now drops incomplete cases and
computes the test statistics from unrounded sums of squares; the printed
table shows the p-value instead of 0 and keeps it within
the Sig. column.ifr_chisq_assoc_test() no longer returns
NaN for the likelihood ratio statistic when a contingency
table contains an empty cell.ifr_chisq_gof_test() applies Yates correction only when
correct = TRUE.ifr_os_t_test() and ifr_ts_ind_ttest() now
compute p-values and confidence intervals from unrounded
statistics.ifr_levene_test() now works with a character grouping
variable and reports the correct number of observations and denominator
degrees of freedom when the data contain missing values.ifr_ts_var_test() now works with a character grouping
variable and requires exactly two groups.ifr_ts_prop_test(), ifr_ts_prop_group()
and ifr_os_prop_test() now reject variables that are not
binary.ifr_ts_paired_ttest() now drops incomplete pairs
instead of failing.ifr_os_t_test(), ifr_ts_ind_ttest() and
ifr_os_var_test() now drop missing values instead of
failing.ifr_mcnemar_test() now requires a 2 x 2 table when
variables are supplied.ifr_runs_test() now reports the number of cases
remaining after drop = TRUE.ifr_chisq_assoc_test() now returns NA for
the phi coefficient when the table is not 2 x 2.Pr(|Z| > |z|).ifr_ts_var_test() now lists the
accepted alternative values, and the README example runs
again.ifr_binom_test() and ifr_binom_calc() now
return and print the two-sided exact p-value, computed with the same
rule as stats::binom.test().ifr_binom_test() now returns an object of class
ifr_binom_test (which also inherits from
ifr_binom_calc), as documented.ifr_ts_var_test() now returns the documented two-sided
p-value.ifr_ts_prop_group() and ifr_ts_prop_calc()
now compute all p-values from the unrounded z statistic.ifr_ts_paired_ttest() now computes p-values and the
confidence interval of the mean difference from the unrounded t
statistic and standard deviation.ifr_binom_test(), ifr_os_prop_test(),
ifr_ts_prop_test(), ifr_ts_prop_group() and
ifr_chisq_gof_test() no longer count missing categorical
values as failures or scale expected counts by missing
observations.ifr_mcnemar_test() caps the exact p-value at 1, bounds
the continuity correction at zero, and defines the no-discordant-pairs
case.ifr_chisq_assoc_test() and
ifr_chisq_gof_test() bound the continuity correction at
zero; the goodness-of-fit deviation and standardized residual use the
signed bounded correction.ifr_ts_paired_ttest() computes the correlation p-value
from the unrounded correlation and the upper tail, so it no longer
exceeds 1 for negative correlations.ifr_levene_test() no longer interchanges Levene’s
mean-centred statistic with Brown and Forsythe’s median-centred
statistic.ifr_ts_ind_ttest() reports the pooled standard
deviation using n1 + n2 - 2 in the denominator.ifr_oneway_anova() handles singleton groups, rejects
designs without residual degrees of freedom, and uses the upper tail for
the p-value so representable p-values are not returned as zero.ifr_oneway_anova() and ifr_ts_ind_ttest()
work when the data contain columns named x or
y.ifr_ts_var_test() requires exactly two columns, or
exactly one outcome column with group_var, and validates
the groups retained after missing values are removed.obs_p as observed, and
describe the runs threshold correctly.library(inferr) no longer contacts CRAN or offers to
update packages when the package is attached.aravindhebbali@rsquaredacademy.com.exam data now points to a
stable page.This is a patch release to fix minor issues.
This is a patch release to fix error on R-devel on Debian and Fedora.
This is a minor release for bug fixes and API changes. We have
completely revamped the API. All the functions now take a
data.frame or tibble as the first argument
followed by the variable names. The variable names need not be
surrounded by single/double quotes anymore. Please view the guide for
more details.
using if/while statement is used with a condition of length greater than 1 will result in a runtime error and not warning (#9)
error in binomial test (#11)
The shiny app has been updated to reflect the changes in the API.
binom_test() accepts non-binary variables (#1).ind_ttest() should throw an error when the grouping
variable has more than 2 levels (#2).ts_prop_test() should accept only binary variables
(#3).var_test() should accept only binary variables for the
group_var input. The number of continuous variables must
also not exceed two. (#4).