# calculate_d: d_s for Between Subjects with Pooled SD Denominator In ViSe: Visualizing Sensitivity

 calculate_d R Documentation

## d_s for Between Subjects with Pooled SD Denominator

### Description

This function displays d for two between subjects groups and gives the central and non-central confidence interval using the pooled standard deviation as the denominator.

### Usage

calculate_d(
m1 = NULL,
m2 = NULL,
sd1 = NULL,
sd2 = NULL,
n1 = NULL,
n2 = NULL,
t = NULL,
model = NULL,
df = NULL,
x_col = NULL,
y_col = NULL,
d = NULL,
a = 0.05,
lower = TRUE
)


### Arguments

 m1 mean group one m2 mean group two sd1 standard deviation group one sd2 standard deviation group two n1 sample size group one n2 sample size group two t optional, calculate d from independent t, you must include n1 and n2 for degrees of freedom model optional, calculate d from t.test for independent t, you must still include n1 and n2 df optional dataframe that includes the x_col and y_col x_col name of the column that contains the factor levels OR a numeric vector of group 1 scores y_col name of the column that contains the dependent score OR a numeric vector of group 2 scores d a previously calculated d value from a study a significance level lower Use this to indicate if you want the lower or upper bound of d for one sided confidence intervals. If d is positive, you generally want lower = TRUE, while negative d values should enter lower = FALSE for the upper bound that is closer to zero.

### Details

To calculate d_s, mean two is subtracted from mean one and divided by the pooled standard deviation.

d_s = \frac{M_1 - M_2}{S_{pooled}}

You should provide one combination of the following:

1: m1 through n2

2: t, n1, n2

3: model, n1, n2

4: df, "x_col", "y_col"

5: x_col, y_col as numeric vectors

6: d, n1, n2

You must provide alpha and lower to ensure the right confidence interval is provided for you.

### Value

Provides the effect size (Cohen's *d*) with associated central and non-central confidence intervals, the *t*-statistic, the confidence intervals associated with the means of each group, as well as the standard deviations and standard errors of the means for each group. The one-tailed confidence interval is also included for sensitivity analyses.

 d effect size dlow noncentral lower level confidence interval of d value dhigh noncentral upper level confidence interval of d value dlow_central central lower level confidence interval of d value dhigh_central central upper level confidence interval of d value done_low noncentral lower bound of one tailed confidence interval done_low_central central lower bound of one tailed confidence interval M1 mean of group one sd1 standard deviation of group one mean se1 standard error of group one mean M1low lower level confidence interval of group one mean M1high upper level confidence interval of group one mean M2 mean of group two sd2 standard deviation of group two mean se2 standard error of group two mean M2low lower level confidence interval of group two mean M2high upper level confidence interval of group two mean spooled pooled standard deviation sepooled pooled standard error n1 sample size of group one n2 sample size of group two df degrees of freedom (n1 - 1 + n2 - 1) t t-statistic p p-value estimate the d statistic and confidence interval in APA style for markdown printing statistic the t-statistic in APA style for markdown printing

### Examples

calculate_d(m1 = 14.37, # neglect mean
sd1 = 10.716, # neglect sd
n1 = 71, # neglect n
m2 = 10.69, # none mean
sd2 = 8.219, # none sd
n2 = 3653, # none n
a = .05, # alpha/confidence interval
lower = TRUE) # lower or upper bound



ViSe documentation built on May 29, 2024, 8:35 a.m.