estimate_mdiff_paired {esci} | R Documentation |
Estimates for a repeated-measures study with two measures of a continuous variable
Description
Returns object
estimate_mdiff_paired
is suitable for a simple paired design
with a continuous outcome variable. It provides estimates and CIs for the
population mean difference between the repeated measures, the standardized
mean difference (SMD; Cohen's d) between the repeated measures, and the
median difference between the repeated measures (raw data only). You can
pass raw data or summary data.
Usage
estimate_mdiff_paired(
data = NULL,
comparison_measure = NULL,
reference_measure = NULL,
comparison_mean = NULL,
comparison_sd = NULL,
reference_mean = NULL,
reference_sd = NULL,
n = NULL,
correlation = NULL,
comparison_measure_name = "Comparison measure",
reference_measure_name = "Reference measure",
conf_level = 0.95,
save_raw_data = TRUE
)
Arguments
data |
For raw data - a data frame or tibble |
comparison_measure |
For raw data - The column name of comparison measure of the outcome variable, or a vector of numeric data |
reference_measure |
For raw data - The column name of the reference measure of the outcome variable, or a vector of numeric data |
comparison_mean |
For summary data, a numeric |
comparison_sd |
For summary data, numeric > 0 |
reference_mean |
For summary data, a numeric |
reference_sd |
For summary data, numeric > 0 |
n |
For summary data, a numeric integer > 0 |
correlation |
For summary data, correlation between measures, a numeric that is > -1 and < 1 |
comparison_measure_name |
For summary data - An optional character label for the comparison measure. Defaults to 'Comparison measure' |
reference_measure_name |
For summary data - An optional character label for the reference measure. Defaults to 'Reference measure' |
conf_level |
The confidence level for the confidence interval. Given in decimal form. Defaults to 0.95. |
save_raw_data |
For raw data; defaults to TRUE; set to FALSE to save memory by not returning raw data in estimate object |
Details
Reach for this function in place of a paired-samples t-test.
Once you generate an estimate with this function, you can visualize
it with plot_mdiff()
and you can test hypotheses with
test_mdiff()
.
The estimated mean differences are from statpsych::ci.mean.ps()
.
The estimated SMDs are from CI_smd_ind_contrast()
.
The estimated median differences are from statpsych::ci.median.ps()
.
Value
Returns object of class esci_estimate
-
overview
-
outcome_variable_name -
-
mean -
-
mean_LL -
-
mean_UL -
-
median -
-
median_LL -
-
median_UL -
-
sd -
-
min -
-
max -
-
q1 -
-
q3 -
-
n -
-
missing -
-
df -
-
mean_SE -
-
median_SE -
-
-
es_mean_difference
-
type -
-
comparison_measure_name -
-
reference_measure_name -
-
effect -
-
effect_size -
-
LL -
-
UL -
-
SE -
-
df -
-
ta_LL -
-
ta_UL -
-
-
es_smd
-
comparison_measure_name -
-
reference_measure_name -
-
effect -
-
effect_size -
-
LL -
-
UL -
-
numerator -
-
denominator -
-
SE -
-
d_biased -
-
df -
-
-
es_r
-
x_variable_name -
-
y_variable_name -
-
effect -
-
effect_size -
-
LL -
-
UL -
-
SE -
-
n -
-
df -
-
ta_LL -
-
ta_UL -
-
-
es_median_difference
-
type -
-
comparison_measure_name -
-
reference_measure_name -
-
effect -
-
effect_size -
-
LL -
-
UL -
-
SE -
-
ta_LL -
-
ta_UL -
-
-
es_mean_ratio
-
comparison_measure_name -
-
reference_measure_name -
-
effect -
-
effect_size -
-
LL -
-
UL -
-
comparison_mean -
-
reference_mean -
-
-
es_median_ratio
-
comparison_measure_name -
-
reference_measure_name -
-
effect -
-
effect_size -
-
LL -
-
UL -
-
comparison_median -
-
reference_median -
-
-
raw_data
-
comparison_measure -
-
reference_measure -
-
Examples
# From raw data
data("data_thomason_1")
estimate_from_raw <- esci::estimate_mdiff_paired(
data = esci::data_thomason_1,
comparison_measure = Posttest,
reference_measure = Pretest
)
# To visualize the estimated median difference (raw data only)
myplot_from_raw <- esci::plot_mdiff(estimate_from_raw, effect_size = "median")
# To conduct a hypothesis test
res_htest_from_raw <- esci::test_mdiff(
estimate_from_raw,
effect_size = "median",
rope = c(-2, 2)
)
sd1 <- 4.28
sd2 <- 3.4
sdiff <- 2.13
cor <- (sd1^2 + sd2^2 - sdiff^2) / (2*sd1*sd2)
estimate_from_summary <- esci::estimate_mdiff_paired(
comparison_mean = 14.25,
comparison_sd = 4.28,
reference_mean = 12.88,
reference_sd = 3.4,
n = 16,
correlation = 0.87072223749,
comparison_measure_name = "After",
reference_measure_name = "Before"
)
# To visualize the estimated mean difference
myplot_from_summary <- esci::plot_mdiff(
estimate_from_summary,
effect_size = "mean"
)
# To conduct a hypothesis test
res_htest_from_summary <- esci::test_mdiff(
estimate_from_summary,
effect_size = "mean",
rope = c(-2, 2)
)