Calculate confidence intervals of mean or difference between means in a data.frame
Source:R/meanCI_sub.R
meanCI_sub.RdCalculate confidence intervals of mean or difference between means in a data.frame
Usage
# S3 method for data.frame
meanCI(x, ...)
meanCI_sub(data = data, x, y, group, paired = FALSE, idx = NULL, ...)Arguments
- x
Name of a categorical or numeric column. If !missing(y), name of continuous variable
- ...
Further arguments to be passed to meanCI
- data
A data.frame
- y
Name of a numeric column
- group
Name of categorical column
- paired
logical
- idx
A vector containing factors or strings in the x columns. These must be quoted (ie. surrounded by quotation marks). The first element will be the control group, so all differences will be computed for every other group and this first group.
Value
An object of class "meanCI" which is a list containing at least the following components:
- data
A tibble containing raw data or a list of numeric vector
- result
A data.frame consists of summary statistics
- call
the matched call
- attr(*,"measure")
character. One of c("mean","unpaired","paired")
Examples
meanCI(acs,age)
#>
#> call: meanCI.data.frame(x = acs, age)
#> method: One sample t-test
#> alternative hypothesis:
#> true mean is not equal to 0
#>
#> Results
#> # A tibble: 1 × 7
#> m se DF lower upper t p
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 63.31155 0.39954 856 62.52736 64.09574 158.46 < 2.2e-16
meanCI(acs,sex,age)
#>
#> call: meanCI.data.frame(x = acs, sex, age)
#> method: Welch Two Sample t-test
#> alternative hypothesis:
#> true unpaired differences in means is not equal to 0
#>
#> Results
#> # A tibble: 1 × 6
#> control test DF CI t p
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 Female Male 596.99 8.07 [95CI 6.52; 9.62] 10.222 < 2.2e-16
meanCI(acs,Dx,age)
#>
#> call: meanCI.data.frame(x = acs, Dx, age)
#> method: Welch Two Sample t-test
#> alternative hypothesis:
#> true unpaired differences in means is not equal to 0
#>
#> Results
#> # A tibble: 2 × 6
#> control test DF CI t p
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 NSTEMI STEMI 300.48 2.22 [95CI -0.17; 4.62] 1.82808 0.06853
#> 2 NSTEMI Unstable Angina 250.10 0.48 [95CI -1.76; 2.73] 0.42479 0.67135
acs %>% select(age) %>% meanCI()
#>
#> call: meanCI.data.frame(x = .)
#> method: One sample t-test
#> alternative hypothesis:
#> true mean is not equal to 0
#>
#> Results
#> # A tibble: 1 × 7
#> m se DF lower upper t p
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 63.31155 0.39954 856 62.52736 64.09574 158.46 < 2.2e-16
acs %>% select(sex,age) %>% meanCI()
#>
#> call: meanCI.data.frame(x = .)
#> method: Welch Two Sample t-test
#> alternative hypothesis:
#> true unpaired differences in means is not equal to 0
#>
#> Results
#> # A tibble: 1 × 6
#> control test DF CI t p
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 Female Male 596.99 8.07 [95CI 6.52; 9.62] 10.222 < 2.2e-16
meanCI(iris,Species,Sepal.Length)
#>
#> call: meanCI.data.frame(x = iris, Species, Sepal.Length)
#> method: Welch Two Sample t-test
#> alternative hypothesis:
#> true unpaired differences in means is not equal to 0
#>
#> Results
#> # A tibble: 2 × 6
#> control test DF CI t p
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 setosa versicolor 86.538 -0.93 [95CI -1.11; -0.75] -10.521 < 2.2e-16
#> 2 setosa virginica 76.516 -1.58 [95CI -1.79; -1.38] -15.386 < 2.2e-16
meanCI(iris,Sepal.Width,Sepal.Length,paired=TRUE)
#>
#> call: meanCI.data.frame(x = iris, Sepal.Width, Sepal.Length, paired = TRUE)
#> method: Paired t-test
#> alternative hypothesis:
#> true paired differences in means is not equal to 0
#>
#> Results
#> # A tibble: 1 × 6
#> control test DF CI t p
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 Sepal.Width Sepal.Length 149 -2.79 [95CI -2.94; -2.63] -34.815 < 2.2e-16
meanCI(iris,Sepal.Length,Sepal.Width)
#>
#> call: meanCI.data.frame(x = iris, Sepal.Length, Sepal.Width)
#> method: Welch Two Sample t-test
#> alternative hypothesis:
#> true unpaired differences in means is not equal to 0
#>
#> Results
#> # A tibble: 1 × 6
#> control test DF CI t p
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 Sepal.Length Sepal.Width 225.68 2.79 [95CI 2.64; 2.94] 36.463 < 2.2e-16
iris %>% select(starts_with("Petal")) %>% meanCI(paired=TRUE)
#>
#> call: meanCI.data.frame(x = ., paired = TRUE)
#> method: Paired t-test
#> alternative hypothesis:
#> true paired differences in means is not equal to 0
#>
#> Results
#> # A tibble: 1 × 6
#> control test DF CI t p
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 Petal.Length Petal.Width 149 2.56 [95CI 2.39; 2.73] 29.797 < 2.2e-16
iris %>% meanCI(paired=TRUE)
#>
#> call: meanCI.data.frame(x = ., paired = TRUE)
#> method: Paired t-test
#> alternative hypothesis:
#> true paired differences in means is not equal to 0
#>
#> Results
#> # A tibble: 3 × 6
#> control test DF CI t p
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 Sepal.Length Sepal.Width 149 2.79 [95CI 2.63; 2.94] " 34.815" < 2.2e-16
#> 2 Sepal.Length Petal.Length 149 2.09 [95CI 1.90; 2.27] " 22.813" < 2.2e-16
#> 3 Sepal.Length Petal.Width 149 4.64 [95CI 4.57; 4.72] "117.539" < 2.2e-16
meanCI(acs,sex,age,Dx,mu=10)
#>
#> call: meanCI.data.frame(x = acs, sex, age, Dx, mu = 10)
#> method: Welch Two Sample t-test
#> alternative hypothesis:
#> true unpaired differences in means is not equal to 10
#>
#> Results
#> # A tibble: 3 × 6
#> control test DF CI t p
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 NSTEMI.Female NSTEMI.Male " 98.798" 9.73 [95CI … -0.1… 0.89…
#> 2 STEMI.Female STEMI.Male "168.691" 9.68 [95CI … -0.2… 0.81…
#> 3 Unstable Angina.Female Unstable Angina.Male "319.818" 6.28 [95CI … -3.4… 0.00…
acs %>% select(sex,TC,TG,HDLC) %>% meanCI(group=sex)
#>
#> call: meanCI.data.frame(x = ., group = sex)
#> method: Welch Two Sample t-test
#> alternative hypothesis:
#> true unpaired differences in means is not equal to 0
#>
#> Results
#> # A tibble: 4 × 6
#> control test DF CI t p
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 Female.TC Female.TG 488.52 69.01 [95CI 58.22; 79.80] 12.564 < 2.2e-16
#> 2 Female.TC Female.HDLC 303.67 149.92 [95CI 143.72; 156.11] 47.617 < 2.2e-16
#> 3 Male.TC Male.TG 800.95 55.46 [95CI 46.54; 64.37] 12.209 < 2.2e-16
#> 4 Male.TC Male.HDLC 618.20 145.50 [95CI 141.57; 149.43] 72.724 < 2.2e-16
acs %>% select(sex,TC,TG,HDLC) %>% meanCI(sex)
#>
#> call: meanCI.data.frame(x = ., sex)
#> method: Welch Two Sample t-test
#> alternative hypothesis:
#> true unpaired differences in means is not equal to 0
#>
#> Results
#> # A tibble: 3 × 6
#> control test DF CI t p
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 TC.Female TC.Male 501.99 5.61 [95CI -1.54; 12.75] " 1.5417" 0.1238
#> 2 TG.Female TG.Male 690.02 -7.95 [95CI -19.98; 4.09] "-1.2961" 0.1954
#> 3 HDLC.Female HDLC.Male 526.44 1.19 [95CI -0.44; 2.82] " 1.4341" 0.1521
iris %>% select(Species,starts_with("Sepal")) %>% meanCI(Species)
#>
#> call: meanCI.data.frame(x = ., Species)
#> method: Welch Two Sample t-test
#> alternative hypothesis:
#> true unpaired differences in means is not equal to 0
#>
#> Results
#> # A tibble: 4 × 6
#> control test DF CI t p
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 Sepal.Length.setosa Sepal.Length.versicolor 86.538 -0.93 [95CI -1… "-10… < 2.…
#> 2 Sepal.Length.setosa Sepal.Length.virginica 76.516 -1.58 [95CI -1… "-15… < 2.…
#> 3 Sepal.Width.setosa Sepal.Width.versicolor 94.698 0.66 [95CI 0.5… " 9… 2.48…
#> 4 Sepal.Width.setosa Sepal.Width.virginica 95.547 0.45 [95CI 0.3… " 6… 4.57…
iris %>% select(Species,starts_with("Sepal")) %>% meanCI(group=Species)
#>
#> call: meanCI.data.frame(x = ., group = Species)
#> method: Welch Two Sample t-test
#> alternative hypothesis:
#> true unpaired differences in means is not equal to 0
#>
#> Results
#> # A tibble: 3 × 6
#> control test DF CI t p
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 setosa.Sepal.Length setosa.Sepal.Width 97.487 1.58 [95CI … 21.5… < 2.…
#> 2 versicolor.Sepal.Length versicolor.Sepal.Width 80.867 3.17 [95CI … 37.0… < 2.…
#> 3 virginica.Sepal.Length virginica.Sepal.Width 72.643 3.61 [95CI … 35.8… < 2.…