[R-meta] Loss to followup over time and calculation of raw mean change (metafor::escalc)

[Dale Steele]

I have data from studies which evaluated patients in each treatment arm at
two time points and report a quantitative outcome.

Between the two time points, a variable number of subjects are lost to
followup.  I would like to calculate a raw mean change and/or standardized
mean change.  I found that metafor::escalc allows only one sample size to
be entered.

Any advice on how to be address the issue of different sample sizes,
specifically when using metafor::escalc?

Example data below:

dat1 <- escalc(measure = "MC", m1i = mean.3, m2i = mean.0,
                                  sd1i = sd.3, sd2i = sd.0,
                                  n1i = n.3, n2i = n0, ri = r, data =
                                  wide_use_c)

wide_use_c <- structure(list(id = c("172507", "172507", "172545", "172545",
"172619"), arm = c("CBT_Educ", "CBT_MI", "MI", "TAU", "Educ"),
    n.0 = c(102, 103, 68, 71, 61), mean.0 = c(37.69, 40.23, 19,
    15.3, 4.3), sd.0 = c(16.06, 14.23, 10.9, 10.1, 2.2), n.3 = c(100,
    101, 41, 54, 53), mean.3 = c(34.53, 31.8, 14.2, 13.7, 4.1
    ), sd.3 = c(19.78, 19.67, 10.8, 11.1, 2.5), r = c(0.9, 0.9,
    0.9, 0.9, 0.9)), class = c("tbl_df", "tbl", "data.frame"), row.names =
c(NA,
-5L), na.action = structure(c(`1` = 1L, `2` = 2L, `3` = 3L, `4` = 4L,
`7` = 7L, `9` = 9L, `11` = 11L, `12` = 12L, `13` = 13L, `14` = 14L,
`19` = 19L, `20` = 20L, `23` = 23L, `24` = 24L, `25` = 25L, `26` = 26L,
`27` = 27L, `28` = 28L, `29` = 29L, `30` = 30L, `35` = 35L, `36` = 36L,
`39` = 39L, `40` = 40L, `41` = 41L, `42` = 42L, `43` = 43L, `47` = 47L,
`48` = 48L, `52` = 52L, `53` = 53L, `54` = 54L, `55` = 55L, `56` = 56L,
`57` = 57L, `60` = 60L, `61` = 61L, `62` = 62L, `63` = 63L, `64` = 64L,
`65` = 65L, `66` = 66L, `69` = 69L, `70` = 70L, `73` = 73L, `74` = 74L
), class = "omit"))

Best.

--Dale

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