Package: interpretCI 0.1.2

interpretCI: Estimate the Confidence Interval and Interpret Step by Step

Estimate confidence intervals for mean, proportion, mean difference for unpaired and paired samples and proportion difference. Plot the confidence intervals. Generate documents explaining the statistical result step by step.

Authors:Keon-Woong Moon [aut, cre]

interpretCI_0.1.2.tar.gz
interpretCI_0.1.2.zip(r-4.7)interpretCI_0.1.2.zip(r-4.6)interpretCI_0.1.2.zip(r-4.5)
interpretCI_0.1.2.tgz(r-4.6-any)interpretCI_0.1.2.tgz(r-4.5-any)
interpretCI_0.1.2.tar.gz(r-4.7-any)interpretCI_0.1.2.tar.gz(r-4.6-any)
interpretCI_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
interpretCI/json (API)

# Install 'interpretCI' in R:

install.packages('interpretCI', repos = c('https://cardiomoon.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/cardiomoon/interpretci/issues

Pkgdown/docs site:https://cardiomoon.github.io

On CRAN:

6.15 score 4 stars 64 scripts 468 downloads 28 exports 93 dependencies

Last updated from:d11e0d16a3. Checks:7 NOTE, 2 OK. Indexed: yes.

Target	Result	Time	Files	Syslog
linux-devel-x86_64	NOTE	170
source / vignettes	OK	316
linux-release-x86_64	NOTE	174
macos-release-arm64	NOTE	94
macos-oldrel-arm64	NOTE	124
windows-devel	NOTE	176
windows-release	NOTE	126
windows-oldrel	NOTE	135
wasm-release	OK	139

Exports:%>%acs draw_n draw_t draw_x2 English english2 estimationPlot1 interpret is.mynumeric isProvided meanCI meanCI_sub meanCI2 meanCI2df meanCI2df1 meanCIplot1 pairPlot pairPlot1 palette2colors propCI propCI_sub rstudio_viewer select show_t_table show_x2_table show_z_table textBox

Dependencies:aplot askpass base64enc beeswarm bslib cachem cli cpp11 crayon data.table datawizard digest dplyr english evaluate farver fastmap flextable fontawesome fontBitstreamVera fontLiberation fontquiver fs gdtools generics ggbeeswarm ggfun ggplot2 ggplotify glue gridGraphics gtable highr hms htmltools insight isoband janitor jquerylib jsonlite knitr labeling lattice lifecycle lubridate magrittr Matrix memoise mime moonBook nortest officer openssl patchwork pillar pkgconfig purrr R6 ragg rappdirs RColorBrewer Rcpp rlang rmarkdown rstudioapi S7 sass scales sjlabelled sjmisc snakecase stringi stringr survival sys systemfonts textshaping tibble tidyr tidyselect timechange tinytex utf8 uuid vctrs vipor viridisLite withr xfun xml2 yaml yulab.utils zip

Confidence interval for the difference between proportions

Problem | Solution | 1. Identify a sample statistic. | 2. Select a confidence level. | 3. Find the margin of error. | Find standard deviation or standard error. | 4. Confidence interval of the proportion | Result of propCI() | Reference

Rendered fromConfidence_interval_for_proportion_difference.Rmdusingknitr::rmarkdown

Last update: 2022-01-27
Started: 2022-01-26

Hypothesis test for the difference between paired means

Problem | Conditions | State the hypotheses | Analyze Sample Data | Standard deviation($s_d$) | standard error(SE) | Select a confidence level. | Degrees of freedom(DF) | Test statistics | 4. Interpret results. | Result of t.test | Result of meanCI() | Reference

Rendered fromHypothesis_test_Paired_Mean_Diff.Rmdusingknitr::rmarkdown

Last update: 2022-01-27
Started: 2022-01-26

R package interpretCI

Package "interpretCI" | Installation | Main functions | 1. meanCI(), propCI() | 2. plot() | 3.interpret() | Basic Usage | 1. Confidence interval of mean | 2. Mean difference in unpaired samples | 3. Mean differences in paired sample | 4. One-sided test | 5. Compare three or more groups | 6. Multiple pairs | 7. Split the data with group argument

Rendered fromPackage_interpretCI.Rmdusingknitr::rmarkdown

Last update: 2022-01-26
Started: 2022-01-26

Confidence interval for a mean

Problem | Confidence interval of mean | Raw data | Sample statistics | Find the margin of error | Confidence interval of the mean | Plot | Result of meanCI() | Reference

Rendered fromConfidence_interval_for_a_mean.Rmdusingknitr::rmarkdown

Last update: 2022-01-26
Started: 2022-01-26

Confidence interval for a proportion

Problem | Confidence interval of a sample proportion | Solution | 1. Identify a sample statistic. | 2. Select a confidence level. | 3. Find the margin of error. | Find standard deviation or standard error. | 4. Confidence interval of the proportion | Result of propCI() | Reference

Rendered fromConfidence_interval_for_a_proportion.Rmdusingknitr::rmarkdown

Last update: 2022-01-26
Started: 2022-01-26

Confidence interval for the paired mean difference

Problem | Solution | Identify a sample statistic. | Standard deviation($s_d$) | standard error(SE) | Select a confidence level. | Degrees of freedom(DF) | Find critical value | Compute margin of error(ME): | Confidence level | Confidence interval of the mean difference | Plot | Result of meanCI() | Reference

Rendered fromConfidence_interval_for_paired_mean_difference.Rmdusingknitr::rmarkdown

Last update: 2022-01-26
Started: 2022-01-26

Confidence interval for the unpaired mean difference

Problem | Confidence interval of mean | Raw data | Identify sample statistics | Select a confidence level. | Find the margin of error | 1. Find standard error. | 2. Find the degree of freedom(df) | 3. Find the critical value | 4. Compute margin of error(ME) | 5. Specify confidence interval | Confidence interval of the mean difference | Plot | Result of meanCI() | Reference

Rendered fromConfidence_interval_for_unpaired_mean_difference.Rmdusingknitr::rmarkdown

Last update: 2022-01-26
Started: 2022-01-26

Hypothesis test for a mean

Given Problem : r ifelse(two.sided,"Two","One")-Tailed Test | Hypothesis Test for a Mean | This approach consists of four steps: | 1. State the hypotheses | 2. Formulate an analysis plan | 3. Analyze sample data. | 4. Interpret results. | Result of meanCI() | Reference

Rendered fromHypothesis_test_for_a_mean.Rmdusingknitr::rmarkdown

Last update: 2022-01-26
Started: 2022-01-26

Hypothesis test for a proportion

Problem | Confidence interval of a sample proportion | Solution | This approach consists of four steps: | 1. State the hypotheses | 2. Formulate an analysis plan | 2. Select a confidence level. | 3. Analyze sample data | 4. Interpret results. | Result of propCI() | Reference

Rendered fromHypothesis_test_for_a_proportion.Rmdusingknitr::rmarkdown

Last update: 2022-01-26
Started: 2022-01-26

Hypothesis test for a difference between means

Given Problem : r ifelse(two.sided,"Two","One")-Tailed Test | Hypothesis test | This approach consists of four steps: | 1. State the hypotheses | 2. Formulate an analysis plan. | 3. Analyze sample data | 4. Interpret results. | Result of meanCI() | Reference

Rendered fromHypothesis_test_Unpaired_Mean_diff.Rmdusingknitr::rmarkdown

Last update: 2022-01-26
Started: 2022-01-26

Hypothesis test for the difference between proportions

Problem | Solution | 1. State the hypotheses | 2. Formulate an analysis plan | 3. Analyze sample data | 4. Interpret results. | Result of propCI() | Reference

Rendered fromHypotheis_test_for_a_difference_between_proportions.Rmdusingknitr::rmarkdown

Last update: 2022-01-26
Started: 2022-01-26

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Demographic data of 857 patients with ACS	acs
Draw normal distribution curve	draw_n
Draw t distribution curve	draw_t
Draw chi-squared distribution curve	draw_x2
Convert numeric to string with uppercase first letter	English
Convert numeric to string	english2
Draw estimation plot1	estimationPlot1
Interpret an object of meanCI	interpret
Decide whether a vector can be treated as a numeric variable	is.mynumeric
Whether the arg is provided in function call	isProvided
Calculate confidence intervals of mean or difference between means	meanCI
Calculate confidence intervals of mean or difference between means in a data.frame	meanCI.data.frame meanCI_sub
Calculate confidence intervals of mean or difference between means	meanCI.default meanCI2
Prepare data to plot from an object of class meanCI	meanCI2df
Extract data from an object of class meanCI	meanCI2df1
Draw meanCI plot for data with single vector	meanCIplot1
Draw a pair plot with an object of class meanCI	pairPlot
Draw a pair plot	pairPlot1
Extract hexadecimal colors from a color palette	palette2colors
S3 method for an object of class "meanCI"	plot.meanCI
S3 method "print" for class "meanCI"	print.meanCI
S3 method for class plotCI	print.plotCI
Calculate confidence intervals of proportion or difference between proportions	propCI
Calculate confidence intervals of proportion or difference between proportions in a data.frame	propCI_sub
Show html file in RStudio viewer or browser	rstudio_viewer
Show t-value table	show_t_table
Show chisquare table	show_x2_table
Show z-value table	show_z_table
Draw textbox	textBox

Usage by other packages (reverse dependencies)