| Type: | Package |
| Title: | Create R Markdown Text for Results in the Style of the American Psychological Association (APA) |
| Version: | 0.1.7 |
| Description: | Create APA style text from analyses for use within R Markdown documents. Descriptive statistics, confidence intervals, and cell sizes are reported. |
| License: | MIT License + file LICENSE |
| Encoding: | UTF-8 |
| Depends: | R (≥ 3.1.2) |
| Imports: | stats, dplyr, cocor |
| Suggests: | apaTables |
| Date: | 2023-05-23 |
| RoxygenNote: | 7.2.3 |
| NeedsCompilation: | no |
| Packaged: | 2023-05-23 10:32:50 UTC; dstanley |
| Author: | David Stanley [aut, cre] |
| Maintainer: | David Stanley <dstanley@uoguelph.ca> |
| Repository: | CRAN |
| Date/Publication: | 2023-05-23 14:02:03 UTC |
Report descriptive statistics for a set of values
Description
Report descriptive statistics for a set of values
Usage
apa.desc(
.data,
.dv = NULL,
show.mean = NULL,
show.sd = NULL,
show.se = NULL,
show.conf.interval = NULL,
show.N = NULL,
number.decimals = NULL
)
Arguments
.data |
A data frame or data frame extension (e.g., tibble) |
.dv |
Name of the dependent variable column |
show.mean |
Show mean (Bool. Default TRUE) |
show.sd |
Show standard deviation (Bool. Default TRUE) |
show.se |
Show standard error (Bool. Default FALSE) |
show.conf.interval |
Show confidence interval (Bool. Default TRUE) |
show.N |
Show number of cases (Bool. Default TRUE) |
number.decimals |
Number of decimals in output |
Value
R Markdown text
Examples
# 2-way ANOVA Example
if (requireNamespace("apaTables", quietly = TRUE)){
library(dplyr)
goggles <- apaTables::goggles
#Main Effect Means: Gender
goggles %>% filter(gender == "Female") %>% apa.desc(attractiveness)
goggles %>% filter(gender == "Male") %>% apa.desc(attractiveness)
# Main Effect Means: Alcohol
goggles %>% filter(alcohol == "None") %>% apa.desc(attractiveness)
goggles %>% filter(alcohol == "2 Pints") %>% apa.desc(attractiveness)
goggles %>% filter(alcohol == "4 Pints") %>% apa.desc(attractiveness)
# Single Cell Mean
goggles %>% filter(alcohol == "4 Pints", gender == "Female") %>%
apa.desc(attractiveness)
}
Report descriptive statistics for a set of values
Description
Report descriptive statistics for a set of values
Usage
apa.ind.t.test(
.data,
.iv,
.dv,
bonferroni.multiplier = 1,
show.mean.difference = TRUE,
show.statistic = NULL,
show.conf.interval = NULL,
number.decimals = NULL,
number.decimals.p = NULL,
var.equal = TRUE,
one.sided = FALSE
)
Arguments
.data |
A data frame or data frame extension (e.g., tibble) |
.iv |
Name of the independent variable column (only 2 levels) |
.dv |
Name of the dependent variable column |
bonferroni.multiplier |
Multiply the p-value by this number to make a bonferroni adjustment |
show.mean.difference |
Show mean difference (Bool. Default TRUE) |
show.statistic |
Show t-value (Bool. Default TRUE) |
show.conf.interval |
Show CI for mean difference (Bool. Default TRUE) |
number.decimals |
Number of decimals used in output (excluding p-value) |
number.decimals.p |
Number of decimals used in p-value output |
var.equal |
(boolean) TRUE or FALSE for cell equal variances |
one.sided |
(boolean) TRUE or FALSE for conducting a one-sided test |
Value
R Markdown text
Examples
if (requireNamespace("apaTables", quietly = TRUE)){
library(dplyr)
goggles <- apaTables::goggles
# one-sided test
goggles %>%
filter(alcohol == "None") %>%
filter(gender == "Female" | gender == "Male") %>%
apa.ind.t.test(gender, attractiveness,
var.equal = TRUE, one.sided = TRUE)
#two-sided test
goggles %>%
filter(alcohol == "None") %>%
filter(gender == "Female" | gender == "Male") %>%
apa.ind.t.test(gender, attractiveness,
var.equal = TRUE, one.sided = FALSE)
#two-sided test with Bonferroni correction (three exploratory tests)
goggles %>%
filter(alcohol == "None") %>%
filter(gender == "Female" | gender == "Male") %>%
apa.ind.t.test(gender, attractiveness,
var.equal = TRUE, one.sided = FALSE,
bonferroni.multiplier = 3)
}
Report r(x,y) correlation in markdown APA style
Description
Report r(x,y) correlation in markdown APA style
Usage
apa.r(
.data,
.x,
.y,
alternative = "two.sided",
method = "pearson",
show.r = TRUE,
show.conf.interval = NULL,
show.N = NULL,
show.p = NULL,
show.statistic = NULL,
number.decimals = NULL,
number.decimals.p = NULL
)
Arguments
.data |
A data frame or data frame extension (e.g., tibble) |
.x |
Name of column in data frame |
.y |
Name of column in data frame |
alternative |
Alternative hypothesis to pass to alternative argument of cor.test. Default is "two.sided" |
method |
Calculation method to pass to alternative argument of cor.test. Default is "pearson" |
show.r |
Show correlation or not (TRUE/FALSE) |
show.conf.interval |
Show confidence interval or not (TRUE/FALSE). Default behavior is TRUE. |
show.N |
Show sample size or not (TRUE/FALSE). Default behavior is TRUE. |
show.p |
Show p-value or not (TRUE/FALSE). Default behavior is TRUE. |
show.statistic |
Show test statistic or not (TRUE/FALSE). Default behavior is TRUE. |
number.decimals |
Number of decimals used in output (excluding p-value) |
number.decimals.p |
Number of decimals used in output for p-value |
Value
R Markdown text
Examples
library(dplyr)
attitude %>% apa.r(rating, advance)
Report difference between correlations in markdown APA style from different samples
Description
Report difference between correlations in markdown APA style from different samples
Usage
apa.r.compare.across.samples(
formula,
data1,
data2,
alternative = "two.sided",
show.conf.interval = NULL,
show.N = NULL,
show.p = NULL,
show.statistic = NULL
)
Arguments
formula |
Formula for comparing correlations |
data1 |
Project data frame 1 name |
data2 |
Project data frame 2 name |
alternative |
Alternative hypothesis to pass to alternative argument of cocor.indep.groups. Default is "two.sided" |
show.conf.interval |
Show confidence interval or not (TRUE/FALSE). Default behavior is TRUE. |
show.N |
Show sample size or not (TRUE/FALSE). Default behavior is TRUE. |
show.p |
Show p-value or not (TRUE/FALSE). Default behavior is TRUE. |
show.statistic |
Show test statistic or not (TRUE/FALSE). Default behavior is TRUE. |
Value
R Markdown text
Examples
# Test difference between r(rating, learning) from dataset: attitude
# and r(weight, height) from dataset: women
apa.r.compare.across.samples(formula = ~ rating + learning | height + weight,
data1 = attitude,
data2 = women)
Report difference between correlations in markdown APA style from different samples
Description
Report difference between correlations in markdown APA style from different samples
Usage
apa.r.compare.across.samples.from.descriptive(
r1,
r2,
n1,
n2,
alternative = "two.sided",
show.conf.interval = NULL,
show.N = NULL,
show.p = NULL,
show.statistic = NULL
)
Arguments
r1 |
Correlation in sample 1 |
r2 |
Correlation in sample 2 |
n1 |
Sample size for sample 1 |
n2 |
Sample size for sample 2 |
alternative |
Alternative hypothesis to pass to alternative argument of cocor.indep.groups. Default is "two.sided" |
show.conf.interval |
Show confidence interval or not (TRUE/FALSE). Default behavior is TRUE. |
show.N |
Show sample size or not (TRUE/FALSE). Default behavior is TRUE. |
show.p |
Show p-value or not (TRUE/FALSE). Default behavior is TRUE. |
show.statistic |
Show test statistic or not (TRUE/FALSE). Default behavior is TRUE. |
Value
R Markdown text
Examples
apa.r.compare.across.samples.from.descriptive(r1 = .3, r2 =.6, n1 = 70, n2 =80)
Report difference in markdown APA style between between correlations within a sample
Description
Report difference in markdown APA style between between correlations within a sample
Usage
apa.r.compare.within.sample(
formula,
data,
test = "pearson1898",
alternative = "two.sided",
show.conf.interval = NULL,
show.N = NULL,
show.p = NULL,
show.statistic = NULL
)
Arguments
formula |
Formula for comparing correlations |
data |
Project data frame name |
test |
Type of significance test. If non-overlapping variables use one of "pearson1898", "dunn1969", "steiger1980", "raghunathan1996", or "silver2004". If overlapping variables use one of pearson1898, hotelling1940, hendrickson1970, williams1959, olkin1967, dunn1969, steiger1980, meng1992, hittner2003. Default is pearson1898. |
alternative |
Alternative hypothesis to pass to alternative argument of cor.test. Default is "two.sided" |
show.conf.interval |
Show confidence interval or not (TRUE/FALSE). Default behavior is TRUE. |
show.N |
Show sample size or not (TRUE/FALSE). Default behavior is TRUE. |
show.p |
Show p-value or not (TRUE/FALSE). Default behavior is TRUE. |
show.statistic |
Show test statistic or not (TRUE/FALSE). Default behavior is TRUE. |
Value
R Markdown text
Examples
# non-overlappling variables example
apa.r.compare.within.sample(data = attitude,
formula = ~ rating + complaints | privileges + learning)
# overlappling variables example
apa.r.compare.within.sample(data = attitude,
formula = ~ rating + complaints | rating + learning)
Create R Markdown Text for Results in the Style of the American Psychological Association (APA)
Description
Create APA style text from analyses for use within R Markdown documents. Descriptive statistics, confidence intervals, and cell sizes are reported.
| Package: | apaText |
| Type: | Package |
| Version: | 0.1.7 |
| Date: | 2023-05-23 |
| License: | MIT |
Author(s)
| Author: | David J. Stanley dstanley@uoguelph.ca |
| Maintainer: | David J. Stanley dstanley@uoguelph.ca |
Create apaText default options for showing confidence intervals etc.. These options will be used unless overridden by local function arguments
Description
Create apaText default options for showing confidence intervals etc.. These options will be used unless overridden by local function arguments
Usage
set.apa.default.options()
Value
A list with options object for apaText
Examples
# You must create an object called apa.default.options
# for options to be used, as per below.
apa.options <- set.apa.default.options()