Mean Difference of Independent Samples with Replicate Weights
repmeandif.RdEstimates the mean difference for a single variable with replicate weights.
For a detailed explanation on how the standard errors are estimated
see repse.
Arguments
- x
a data frame produced by
repmeanfor a single variable or an object produced byleaguetable.
Examples
# Creation of replicate weights
RW <- repcreate(df = repdata, # the data frame with all the information
wt = "wt", # the total weights column name
jkzone = "jkzones", # the jkzones column name
jkrep = "jkrep", # the jkreps column name
repwtname = "REPWT", # the desired name for the rep weights
reps = 50, # the number of replications
method = "ICILS") # the name of the method aka the study name
### Groups ----
# One variable
reme <- repmean(x = c("item01"),
PV = FALSE,
repwt = RW, wt = "wt", df = repdata,
method = "ICILS",var = "ML",
group = "GROUP",
exclude = "GR2") # GR2 will not be used for Pooled nor Composite
repmeandif(reme)
#> group1 group2 dif se tvalue df pvalue
#> 1 Pooled Pooled 0.00000 0.01648 0.00000 5982 1.00000
#> 2 Pooled Composite 0.00009 0.01650 0.00545 NA NA
#> 3 Pooled GR1 -0.01593 0.01933 -0.82411 4497 0.40992
#> 4 Pooled GR2 0.02005 0.02297 0.87288 4481 0.38278
#> 5 Pooled GR3 0.01611 0.02107 0.76459 4475 0.44455
#> 6 Composite Pooled -0.00009 0.01650 -0.00545 NA NA
#> 7 Composite Composite 0.00000 0.01652 0.00000 NA NA
#> 8 Composite GR1 -0.01602 0.01934 -0.82834 NA NA
#> 9 Composite GR2 0.01997 0.02298 0.86902 NA NA
#> 10 Composite GR3 0.01602 0.02108 0.75996 NA NA
#> 11 GR1 Pooled 0.01593 0.01933 0.82411 4497 0.40992
#> 12 GR1 Composite 0.01602 0.01934 0.82834 NA NA
#> 13 GR1 GR1 0.00000 0.02180 0.00000 3012 1.00000
#> 14 GR1 GR2 0.03599 0.02509 1.43444 2996 0.15155
#> 15 GR1 GR3 0.03204 0.02336 1.37158 2990 0.17030
#> 16 GR2 Pooled -0.02005 0.02297 -0.87288 4481 0.38278
#> 17 GR2 Composite -0.01997 0.02298 -0.86902 NA NA
#> 18 GR2 GR1 -0.03599 0.02509 -1.43444 2996 0.15155
#> 19 GR2 GR2 0.00000 0.02799 0.00000 2980 1.00000
#> 20 GR2 GR3 -0.00395 0.02645 -0.14934 2974 0.88130
#> 21 GR3 Pooled -0.01611 0.02107 -0.76459 4475 0.44455
#> 22 GR3 Composite -0.01602 0.02108 -0.75996 NA NA
#> 23 GR3 GR1 -0.03204 0.02336 -1.37158 2990 0.17030
#> 24 GR3 GR2 0.00395 0.02645 0.14934 2974 0.88130
#> 25 GR3 GR3 0.00000 0.02482 0.00000 2968 1.00000
# One PV variable
reme <- repmean(x = paste0("Math",1:5),
PV = TRUE, # if set to TRUE, PVs will be treated as separate variables
repwt = RW, wt = "wt", df = repdata,
method = "ICILS",var = "ML",
group = "GROUP",
exclude = "GR2") # GR2 will not be used for Pooled nor Composite
repmeandif(reme)
#> group1 group2 dif se tvalue df pvalue
#> 1 Pooled Pooled 0.00000 0.03012 0.00000 6666 1.00000
#> 2 Pooled Composite 0.00059 0.03440 0.01715 NA NA
#> 3 Pooled GR1 0.59181 0.04482 13.20415 4999 0.00000
#> 4 Pooled GR2 -0.02003 0.03207 -0.62457 4998 0.53228
#> 5 Pooled GR3 -0.59064 0.04262 -13.85828 4999 0.00000
#> 6 Composite Pooled -0.00059 0.03440 -0.01715 NA NA
#> 7 Composite Composite 0.00000 0.03819 0.00000 NA NA
#> 8 Composite GR1 0.59122 0.04779 12.37121 NA NA
#> 9 Composite GR2 -0.02062 0.03611 -0.57103 NA NA
#> 10 Composite GR3 -0.59122 0.04574 -12.92567 NA NA
#> 11 GR1 Pooled -0.59181 0.04482 -13.20415 4999 0.00000
#> 12 GR1 Composite -0.59122 0.04779 -12.37121 NA NA
#> 13 GR1 GR1 0.00000 0.05576 0.00000 3332 1.00000
#> 14 GR1 GR2 -0.61185 0.04614 -13.26073 3331 0.00000
#> 15 GR1 GR3 -1.18245 0.05402 -21.88912 3332 0.00000
#> 16 GR2 Pooled 0.02003 0.03207 0.62457 4998 0.53228
#> 17 GR2 Composite 0.02062 0.03611 0.57103 NA NA
#> 18 GR2 GR1 0.61185 0.04614 13.26073 3331 0.00000
#> 19 GR2 GR2 0.00000 0.03390 0.00000 3330 1.00000
#> 20 GR2 GR3 -0.57060 0.04402 -12.96229 3331 0.00000
#> 21 GR3 Pooled 0.59064 0.04262 13.85828 4999 0.00000
#> 22 GR3 Composite 0.59122 0.04574 12.92567 NA NA
#> 23 GR3 GR1 1.18245 0.05402 21.88912 3332 0.00000
#> 24 GR3 GR2 0.57060 0.04402 12.96229 3331 0.00000
#> 25 GR3 GR3 0.00000 0.05221 0.00000 3332 1.00000
### Groups and By ----
# One variable
reme <- repmean(x = c("item01"),
PV = FALSE,
repwt = RW, wt = "wt", df = repdata,
method = "ICILS",var = "ML",
group = "GROUP",
by = "GENDER", # results will be separated by GENDER
exclude = "GR2") # GR2 will not be used for Pooled nor Composite
repmeandif(reme)
#> $ALL
#> group1 group2 dif se tvalue df pvalue
#> 1 Pooled Pooled 0.00000 0.01648 0.00000 5982 1.00000
#> 2 Pooled Composite 0.00009 0.01650 0.00545 NA NA
#> 3 Pooled GR1 -0.01593 0.01933 -0.82411 4497 0.40992
#> 4 Pooled GR2 0.02005 0.02297 0.87288 4481 0.38278
#> 5 Pooled GR3 0.01611 0.02107 0.76459 4475 0.44455
#> 6 Composite Pooled -0.00009 0.01650 -0.00545 NA NA
#> 7 Composite Composite 0.00000 0.01652 0.00000 NA NA
#> 8 Composite GR1 -0.01602 0.01934 -0.82834 NA NA
#> 9 Composite GR2 0.01997 0.02298 0.86902 NA NA
#> 10 Composite GR3 0.01602 0.02108 0.75996 NA NA
#> 11 GR1 Pooled 0.01593 0.01933 0.82411 4497 0.40992
#> 12 GR1 Composite 0.01602 0.01934 0.82834 NA NA
#> 13 GR1 GR1 0.00000 0.02180 0.00000 3012 1.00000
#> 14 GR1 GR2 0.03599 0.02509 1.43444 2996 0.15155
#> 15 GR1 GR3 0.03204 0.02336 1.37158 2990 0.17030
#> 16 GR2 Pooled -0.02005 0.02297 -0.87288 4481 0.38278
#> 17 GR2 Composite -0.01997 0.02298 -0.86902 NA NA
#> 18 GR2 GR1 -0.03599 0.02509 -1.43444 2996 0.15155
#> 19 GR2 GR2 0.00000 0.02799 0.00000 2980 1.00000
#> 20 GR2 GR3 -0.00395 0.02645 -0.14934 2974 0.88130
#> 21 GR3 Pooled -0.01611 0.02107 -0.76459 4475 0.44455
#> 22 GR3 Composite -0.01602 0.02108 -0.75996 NA NA
#> 23 GR3 GR1 -0.03204 0.02336 -1.37158 2990 0.17030
#> 24 GR3 GR2 0.00395 0.02645 0.14934 2974 0.88130
#> 25 GR3 GR3 0.00000 0.02482 0.00000 2968 1.00000
#>
#> $`GENDER==0`
#> group1 group2 dif se tvalue df pvalue
#> 1 Pooled Pooled 0.00000 0.02565 0.00000 2914 1.00000
#> 2 Pooled Composite -0.00001 0.02524 -0.00040 NA NA
#> 3 Pooled GR1 0.00655 0.03062 0.21391 2190 0.83064
#> 4 Pooled GR2 0.04650 0.03437 1.35292 2216 0.17622
#> 5 Pooled GR3 -0.00658 0.03086 -0.21322 2180 0.83117
#> 6 Composite Pooled 0.00001 0.02524 0.00040 NA NA
#> 7 Composite Composite 0.00000 0.02482 0.00000 NA NA
#> 8 Composite GR1 0.00656 0.03028 0.21664 NA NA
#> 9 Composite GR2 0.04652 0.03406 1.36583 NA NA
#> 10 Composite GR3 -0.00656 0.03052 -0.21494 NA NA
#> 11 GR1 Pooled -0.00655 0.03062 -0.21391 2190 0.83064
#> 12 GR1 Composite -0.00656 0.03028 -0.21664 NA NA
#> 13 GR1 GR1 0.00000 0.03489 0.00000 1466 1.00000
#> 14 GR1 GR2 0.03996 0.03822 1.04553 1492 0.29595
#> 15 GR1 GR3 -0.01312 0.03511 -0.37368 1456 0.70869
#> 16 GR2 Pooled -0.04650 0.03437 -1.35292 2216 0.17622
#> 17 GR2 Composite -0.04652 0.03406 -1.36583 NA NA
#> 18 GR2 GR1 -0.03996 0.03822 -1.04553 1492 0.29595
#> 19 GR2 GR2 0.00000 0.04129 0.00000 1518 1.00000
#> 20 GR2 GR3 -0.05308 0.03842 -1.38157 1482 0.16731
#> 21 GR3 Pooled 0.00658 0.03086 0.21322 2180 0.83117
#> 22 GR3 Composite 0.00656 0.03052 0.21494 NA NA
#> 23 GR3 GR1 0.01312 0.03511 0.37368 1456 0.70869
#> 24 GR3 GR2 0.05308 0.03842 1.38157 1482 0.16731
#> 25 GR3 GR3 0.00000 0.03532 0.00000 1446 1.00000
#>
#> $`GENDER==1`
#> group1 group2 dif se tvalue df pvalue
#> 1 Pooled Pooled 0.00000 0.02314 0.00000 3066 1.00000
#> 2 Pooled Composite 0.00032 0.02333 0.01372 NA NA
#> 3 Pooled GR1 -0.03716 0.02849 -1.30432 2305 0.19226
#> 4 Pooled GR2 -0.00605 0.03196 -0.18930 2263 0.84988
#> 5 Pooled GR3 0.03779 0.02882 1.31124 2293 0.18991
#> 6 Composite Pooled -0.00032 0.02333 -0.01372 NA NA
#> 7 Composite Composite 0.00000 0.02352 0.00000 NA NA
#> 8 Composite GR1 -0.03747 0.02864 -1.30831 NA NA
#> 9 Composite GR2 -0.00637 0.03210 -0.19844 NA NA
#> 10 Composite GR3 0.03747 0.02897 1.29341 NA NA
#> 11 GR1 Pooled 0.03716 0.02849 1.30432 2305 0.19226
#> 12 GR1 Composite 0.03747 0.02864 1.30831 NA NA
#> 13 GR1 GR1 0.00000 0.03298 0.00000 1544 1.00000
#> 14 GR1 GR2 0.03111 0.03602 0.86369 1502 0.38790
#> 15 GR1 GR3 0.07495 0.03326 2.25346 1532 0.02437
#> 16 GR2 Pooled 0.00605 0.03196 0.18930 2263 0.84988
#> 17 GR2 Composite 0.00637 0.03210 0.19844 NA NA
#> 18 GR2 GR1 -0.03111 0.03602 -0.86369 1502 0.38790
#> 19 GR2 GR2 0.00000 0.03883 0.00000 1460 1.00000
#> 20 GR2 GR3 0.04384 0.03628 1.20838 1490 0.22709
#> 21 GR3 Pooled -0.03779 0.02882 -1.31124 2293 0.18991
#> 22 GR3 Composite -0.03747 0.02897 -1.29341 NA NA
#> 23 GR3 GR1 -0.07495 0.03326 -2.25346 1532 0.02437
#> 24 GR3 GR2 -0.04384 0.03628 -1.20838 1490 0.22709
#> 25 GR3 GR3 0.00000 0.03355 0.00000 1520 1.00000
#>
# One PV variable
reme <- repmean(x = paste0("Math",1:5),
PV = TRUE, # if set to TRUE, PVs will be treated as separate variables
repwt = RW, wt = "wt", df = repdata,
method = "ICILS",var = "ML",
group = "GROUP",
by = "GENDER", # results will be separated by GENDER
exclude = "GR2") # GR2 will not be used for Pooled nor Composite
repmeandif(reme)
#> $ALL
#> group1 group2 dif se tvalue df pvalue
#> 1 Pooled Pooled 0.00000 0.03012 0.00000 6666 1.00000
#> 2 Pooled Composite 0.00059 0.03440 0.01715 NA NA
#> 3 Pooled GR1 0.59181 0.04482 13.20415 4999 0.00000
#> 4 Pooled GR2 -0.02003 0.03207 -0.62457 4998 0.53228
#> 5 Pooled GR3 -0.59064 0.04262 -13.85828 4999 0.00000
#> 6 Composite Pooled -0.00059 0.03440 -0.01715 NA NA
#> 7 Composite Composite 0.00000 0.03819 0.00000 NA NA
#> 8 Composite GR1 0.59122 0.04779 12.37121 NA NA
#> 9 Composite GR2 -0.02062 0.03611 -0.57103 NA NA
#> 10 Composite GR3 -0.59122 0.04574 -12.92567 NA NA
#> 11 GR1 Pooled -0.59181 0.04482 -13.20415 4999 0.00000
#> 12 GR1 Composite -0.59122 0.04779 -12.37121 NA NA
#> 13 GR1 GR1 0.00000 0.05576 0.00000 3332 1.00000
#> 14 GR1 GR2 -0.61185 0.04614 -13.26073 3331 0.00000
#> 15 GR1 GR3 -1.18245 0.05402 -21.88912 3332 0.00000
#> 16 GR2 Pooled 0.02003 0.03207 0.62457 4998 0.53228
#> 17 GR2 Composite 0.02062 0.03611 0.57103 NA NA
#> 18 GR2 GR1 0.61185 0.04614 13.26073 3331 0.00000
#> 19 GR2 GR2 0.00000 0.03390 0.00000 3330 1.00000
#> 20 GR2 GR3 -0.57060 0.04402 -12.96229 3331 0.00000
#> 21 GR3 Pooled 0.59064 0.04262 13.85828 4999 0.00000
#> 22 GR3 Composite 0.59122 0.04574 12.92567 NA NA
#> 23 GR3 GR1 1.18245 0.05402 21.88912 3332 0.00000
#> 24 GR3 GR2 0.57060 0.04402 12.96229 3331 0.00000
#> 25 GR3 GR3 0.00000 0.05221 0.00000 3332 1.00000
#>
#> $`GENDER==0`
#> group1 group2 dif se tvalue df pvalue
#> 1 Pooled Pooled 0.00000 0.06279 0.00000 3272 1.00000
#> 2 Pooled Composite 0.00098 0.05847 0.01676 NA NA
#> 3 Pooled GR1 0.61707 0.06295 9.80254 2454 0.00000
#> 4 Pooled GR2 -0.04332 0.05662 -0.76510 2481 0.44428
#> 5 Pooled GR3 -0.61512 0.07595 -8.09901 2453 0.00000
#> 6 Composite Pooled -0.00098 0.05847 -0.01676 NA NA
#> 7 Composite Composite 0.00000 0.05380 0.00000 NA NA
#> 8 Composite GR1 0.61610 0.05864 10.50648 NA NA
#> 9 Composite GR2 -0.04430 0.05178 -0.85554 NA NA
#> 10 Composite GR3 -0.61610 0.07242 -8.50732 NA NA
#> 11 GR1 Pooled -0.61707 0.06295 -9.80254 2454 0.00000
#> 12 GR1 Composite -0.61610 0.05864 -10.50648 NA NA
#> 13 GR1 GR1 0.00000 0.06311 0.00000 1636 1.00000
#> 14 GR1 GR2 -0.66040 0.05679 -11.62881 1663 0.00000
#> 15 GR1 GR3 -1.23219 0.07608 -16.19598 1635 0.00000
#> 16 GR2 Pooled 0.04332 0.05662 0.76510 2481 0.44428
#> 17 GR2 Composite 0.04430 0.05178 0.85554 NA NA
#> 18 GR2 GR1 0.66040 0.05679 11.62881 1663 0.00000
#> 19 GR2 GR2 0.00000 0.04968 0.00000 1690 1.00000
#> 20 GR2 GR3 -0.57180 0.07093 -8.06147 1662 0.00000
#> 21 GR3 Pooled 0.61512 0.07595 8.09901 2453 0.00000
#> 22 GR3 Composite 0.61610 0.07242 8.50732 NA NA
#> 23 GR3 GR1 1.23219 0.07608 16.19598 1635 0.00000
#> 24 GR3 GR2 0.57180 0.07093 8.06147 1662 0.00000
#> 25 GR3 GR3 0.00000 0.08715 0.00000 1634 1.00000
#>
#> $`GENDER==1`
#> group1 group2 dif se tvalue df pvalue
#> 1 Pooled Pooled 0.00000 0.07298 0.00000 3392 1.00000
#> 2 Pooled Composite 0.00024 0.06774 0.00354 NA NA
#> 3 Pooled GR1 0.56707 0.08799 6.44471 2543 0.00000
#> 4 Pooled GR2 0.03155 0.07040 0.44815 2515 0.65408
#> 5 Pooled GR3 -0.56659 0.07272 -7.79139 2544 0.00000
#> 6 Composite Pooled -0.00024 0.06774 -0.00354 NA NA
#> 7 Composite Composite 0.00000 0.06207 0.00000 NA NA
#> 8 Composite GR1 0.56683 0.08370 6.77216 NA NA
#> 9 Composite GR2 0.03131 0.06496 0.48199 NA NA
#> 10 Composite GR3 -0.56683 0.06746 -8.40246 NA NA
#> 11 GR1 Pooled -0.56707 0.08799 -6.44471 2543 0.00000
#> 12 GR1 Composite -0.56683 0.08370 -6.77216 NA NA
#> 13 GR1 GR1 0.00000 0.10080 0.00000 1694 1.00000
#> 14 GR1 GR2 -0.53552 0.08587 -6.23640 1666 0.00000
#> 15 GR1 GR3 -1.13367 0.08778 -12.91490 1695 0.00000
#> 16 GR2 Pooled -0.03155 0.07040 -0.44815 2515 0.65408
#> 17 GR2 Composite -0.03131 0.06496 -0.48199 NA NA
#> 18 GR2 GR1 0.53552 0.08587 6.23640 1666 0.00000
#> 19 GR2 GR2 0.00000 0.06773 0.00000 1638 1.00000
#> 20 GR2 GR3 -0.59814 0.07014 -8.52780 1667 0.00000
#> 21 GR3 Pooled 0.56659 0.07272 7.79139 2544 0.00000
#> 22 GR3 Composite 0.56683 0.06746 8.40246 NA NA
#> 23 GR3 GR1 1.13367 0.08778 12.91490 1695 0.00000
#> 24 GR3 GR2 0.59814 0.07014 8.52780 1667 0.00000
#> 25 GR3 GR3 0.00000 0.07246 0.00000 1696 1.00000
#>