Computes the paired two-sample Student's t-test for each feature.
See the Details section below for further information.
Usage
rowPairedT(
x,
g,
null = 0,
alternative = c("two.sided", "greater", "less"),
conf.level = 0.95
)Arguments
- x
matrixordata.frame.- g
a vector or factor object giving the group for the corresponding elements of
x.- null
numerical value or numeric vector of length
nrow(x). The true values of the difference in means between the two groups of observations for each row.- alternative
character string or vector of length
nrow(x). The alternative hypothesis for each row ofx. Values must be one of"two.sided"(default),"greater"or"less".- conf.level
numerical value or numeric vector of length
nrow(x). The confidence levels of the intervals. All values must be in the range of \([0:1]\) orNA.
Value
A list containing two elements:
- statistic
A numeric vector, the values of the test statistic
- significance
A numeric vector, the p-values of the selected test
Details
It is a wrapper to row_t_paired
function.
Examples
#Seed
set.seed(1010)
#Data
x = matrix(rnorm(100 * 20), 100, 20)
g = c(rep(0,10),rep(1,10))
#Compute
rowPairedT(x = x, g = g)
#> $statistic
#> [1] 0.105846642 -1.226066457 0.933934421 -1.188231761 3.464396651
#> [6] 0.842077479 1.144499292 -0.173302153 -0.806080402 0.558394598
#> [11] -0.985378713 -2.713690594 -0.653815335 -1.654687005 1.031975003
#> [16] -0.494881934 0.449574782 -1.803658453 0.215272438 0.139165914
#> [21] -0.356861393 3.426546800 -2.032570216 -1.047425674 -0.579835348
#> [26] 0.616875137 0.575104052 -0.477912629 -1.320900894 -1.919637167
#> [31] -0.704886562 4.363388296 2.098441892 -0.314608823 -1.731951723
#> [36] 1.018514762 -0.296800214 -0.915867468 -1.483291946 -0.999254476
#> [41] -0.005859077 -0.279279608 -1.187075604 0.344343077 0.938509422
#> [46] -0.529167965 1.942391536 1.240516329 1.168882007 3.679833178
#> [51] 2.225412187 1.375351762 -1.325044174 0.874555960 1.228400760
#> [56] -2.935832351 0.290564498 0.135850613 1.497595462 -1.522978283
#> [61] 0.894265416 -2.442443525 0.430641608 0.057264512 -0.179048797
#> [66] -1.399424743 -0.858911640 -2.472199259 -1.161983005 -0.187989620
#> [71] -0.093156228 -2.679082345 -0.308042742 -0.236298424 -0.358293729
#> [76] -1.906006842 -0.039285775 1.956415638 -0.237303229 1.009791671
#> [81] -0.706780344 -0.920758455 0.113955442 -0.274247407 0.648897152
#> [86] -0.502341383 1.162301553 -0.050237610 0.285373393 -1.281896029
#> [91] 1.014856566 2.065955751 -0.986794564 1.038803611 1.457049907
#> [96] 0.800263487 -0.790084646 -1.367524716 1.205469111 -1.789471257
#>
#> $significance
#> [1] 0.918025662 0.251285313 0.374715471 0.265150997 0.007111320 0.421556589
#> [7] 0.281941054 0.866248992 0.440974411 0.590194360 0.350185799 0.023852928
#> [13] 0.529579909 0.132373864 0.329017211 0.632539543 0.663648866 0.104782066
#> [19] 0.834354129 0.892383391 0.729419519 0.007549351 0.072632160 0.322216585
#> [25] 0.576251176 0.552600390 0.579312274 0.644106442 0.219132110 0.087107106
#> [31] 0.498715006 0.001814482 0.065283135 0.760229868 0.117325052 0.335030238
#> [37] 0.773354682 0.383620146 0.172147130 0.343778169 0.995452976 0.786341966
#> [43] 0.265584277 0.738497450 0.372484537 0.609490560 0.083986374 0.246148506
#> [49] 0.272477973 0.005076784 0.053092953 0.202284235 0.217809707 0.404548850
#> [55] 0.250449590 0.016598828 0.777968661 0.894929437 0.168463117 0.162096094
#> [61] 0.394465405 0.037215173 0.676858202 0.955585711 0.861865313 0.195195361
#> [67] 0.412680398 0.035442158 0.275129352 0.855055017 0.927820245 0.025243991
#> [73] 0.765059856 0.818491190 0.728383631 0.089028641 0.969520207 0.082116053
#> [79] 0.817735236 0.338971204 0.497592376 0.381194616 0.911774743 0.790085272
#> [85] 0.532611568 0.627487859 0.275006476 0.961030320 0.781816739 0.231914966
#> [91] 0.336678726 0.068813325 0.349527929 0.325998229 0.179089885 0.444167975
#> [97] 0.449793471 0.204636031 0.258758723 0.107160561
#>