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Bland-Altman analysis

Source: R/bland_altman.R
s_bland_altman.Rd

[Experimental]

Statistics function that uses the Bland-Altman method to assess the agreement between two numerical vectors and calculates a variety of statistics.

Usage 

s_bland_altman(x, y, conf_level = 0.95)

Arguments

x

(numeric)
vector of numbers we want to analyze.

y

(numeric)
vector of numbers we want to analyze, to be compared with x.

conf_level

(proportion)
confidence level of the interval.

Value

A named list of the following elements:

  • df

  • difference_mean

  • ci_mean

  • difference_sd

  • difference_se

  • upper_agreement_limit

  • lower_agreement_limit

  • agreement_limit_se

  • upper_agreement_limit_ci

  • lower_agreement_limit_ci

  • t_value

  • n

Examples 

x <- seq(1, 60, 5)
y <- seq(5, 50, 4)

s_bland_altman(x, y, conf_level = 0.9)
#> $df
#>    average difference
#> 1      3.0         -4
#> 2      7.5         -3
#> 3     12.0         -2
#> 4     16.5         -1
#> 5     21.0          0
#> 6     25.5          1
#> 7     30.0          2
#> 8     34.5          3
#> 9     39.0          4
#> 10    43.5          5
#> 11    48.0          6
#> 12    52.5          7
#> 
#> $difference_mean
#> [1] 1.5
#> 
#> $ci_mean
#> [1] -0.3692162  3.3692162
#> 
#> $difference_sd
#> [1] 3.605551
#> 
#> $difference_se
#> [1] 1.040833
#> 
#> $upper_agreement_limit
#> [1] 7.430604
#> 
#> $lower_agreement_limit
#> [1] -4.430604
#> 
#> $agreement_limit_se
#> [1] 1.802776
#> 
#> $upper_agreement_limit_ci
#> [1]  4.193027 10.668181
#> 
#> $lower_agreement_limit_ci
#> [1] -7.668181 -1.193027
#> 
#> $t_value
#> [1] 1.795885
#> 
#> $n
#> [1] 12
#>