Package: RoundingMatters 0.1.0

RoundingMatters: Tools for adjusting for rounding problems in metastudies about p-hacking and publication bias

Tools for adjusting for rounding problems in metastudies about p-hacking and publication bias

Authors:Sebastian Kranz, Peter Puetz

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RoundingMatters.pdf |RoundingMatters.html✨
RoundingMatters/json (API)

# Install 'RoundingMatters' in R:
install.packages('RoundingMatters', repos = c('https://skranz.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/skranz/roundingmatters/issues

On CRAN:

1.70 score 8 scripts 42 exports 37 dependencies

Last updated 3 years agofrom:ca9b1e2a08 (on main). Checks:OK: 1 WARNING: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 30 2024
R-4.5-winWARNINGSep 30 2024
R-4.5-linuxWARNINGSep 30 2024
R-4.4-winWARNINGSep 30 2024
R-4.4-macWARNINGSep 30 2024
R-4.3-winWARNINGSep 30 2024
R-4.3-macWARNINGSep 30 2024

Exports:absz.densityabsz.density.ratioas.perccompute_abszdensitycompute.stats.for.all.hderound.z.density.adjustderound.z.uniformdsr.ab.dfdsr.ab.for.obsdsr.dist.for.obsdsr.mark.obsexample.dsrexamples.digit.toolshas.colhas.rounding.riskis.truemake.z.pdfmin.max.znum.decinum.sig.digitsprobitmfxweightsprobitweightedquick.dfrightmost.sig.digitrounding.risk.s.thresholdsrounding.risksrounding.risks.summarysample.uniform.z.deroundset.last.digit.zerosignificandstat_abszdensityStatAbsZDensitystr.betweenstr.left.ofstr.right.ofstudy.with.deroundinguniform.ab.dfuniform.ab.for.obswindow.binom.ciwindow.binom.testwindow.binom.test.2swindow.t.ci

Dependencies:clicolorspacecpp11dplyrfansifarvergenericsggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigpurrrR6RColorBrewerrestorepointrlangscalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
Density estimates for absolute z-statistics assuming that z-statistics are symmetrically distributed around 0absz.density
Perform kernel estimates of two densities of absolute z-statistics and their ratio.absz.density.ratio
Convert numbers like 0.421 to 42.1%as.perc
Draw derounded z assuming missing digits of mu and sigma are uniformly distributed, but adjust for estimated density of z using rejection samplingderound.z.density.adjust
Draw derounded z assuming missing digits of mu and sigma are uniformly distributedderound.z.uniform
Create an ab.df for the dsr approachdsr.ab.df
Finds observations in dat for which we shall perform dsr adjustmentdsr.mark.obs
Compute a normalized pdf from a vector of z-statisticsmake.z.pdf
Compute minimum and maximum possible values of z given rounded mu and sigmamin.max.z
Get the number of significand digits of a floating point number using the character presentation of those numbers of Rnum.deci
Get the number of significand digits of a floating point number using the character presentation of those numbers of Rnum.sig.digits
Get the last significant digit(s) of a floating point numberrightmost.sig.digit
Compute thresholds for the significant s of the reported standard deviation such that we can rule-out the errors: misclassification, wrong inclusion, wrong exclusionrounding.risk.s.thresholds
Assess for observations with reported z-statistic z and a signficand of s for the standard error whether it is at risk of the errors: misclassification, wrong inclusion, wrong exclusionrounding.risks
Summary statistics for rounding risks for different thresholdsrounding.risks.summary
Sample derounded z from the uniformely derounded distributon for a given single value of mu and sigmasample.uniform.z.deround
Sets the last digit of a number x to zeroset.last.digit.zero
Get the significands of a numeric vector using the character presentation of those numbers of Rsignificand
ggplot2 density lines for absolute z-statistics assuming that they are symmetrically distributed around 0stat_abszdensity
Analysis with derounded z-statistics for different window half-widths around z0study.with.derounding
Apply on windows one-sided binomiminal test with H0: z <= z0window.binom.test
Apply on windows two sided binomiminal test with H0: z = z0window.binom.test.2s
Window function returning estimated probability that a z-statistic is above a threshold z0 in a window with half-width h around z0 and t-test confidence intervalswindow.t.ci