data/BCG.R

In mikewlcheung/metasem: Meta-Analysis using Structural Equation Modeling

BCG <-
structure(list(Trial = 1:13, Author = structure(c(1L, 5L, 8L, 
7L, 6L, 9L, 11L, 10L, 2L, 8L, 3L, 4L, 3L), .Label = c("Aronson", 
"Coetzee & Berjak", "Comstock et al", "Comstock & Webster", "Ferguson & Simes", 
"Frimodt-Moller et al", "Hart & Sutherland", "Rosenthal et al", 
"Stein & Aronson", "TPT Madras", "Vandiviere et al"), class = "factor"), 
    Year = c(1948L, 1949L, 1960L, 1977L, 1973L, 1953L, 1973L, 
    1980L, 1968L, 1961L, 1974L, 1969L, 1976L), VD = c(4L, 6L, 
    3L, 62L, 33L, 180L, 8L, 505L, 29L, 17L, 186L, 5L, 27L), VWD = c(119L, 
    300L, 228L, 13536L, 5036L, 1361L, 2537L, 87886L, 7470L, 1699L, 
    50448L, 2493L, 16886L), NVD = c(11L, 29L, 11L, 248L, 47L, 
    372L, 10L, 499L, 45L, 65L, 141L, 3L, 29L), NVWD = c(128L, 
    274L, 209L, 12619L, 5761L, 1079L, 619L, 87892L, 7232L, 1600L, 
    27197L, 2338L, 17825L), Latitude = c(44L, 55L, 42L, 52L, 
    13L, 44L, 19L, 13L, 27L, 42L, 18L, 33L, 33L), Allocation = structure(c(2L, 
    2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 3L), .Label = c("alternate", 
    "random", "systematic"), class = "factor"), ln_OR = c(-0.938694140870392, 
    -1.66619072902655, -1.38629436111989, -1.45644354931298, 
    -0.219141085675433, -0.958122040776268, -1.6337758382289, 
    0.0120206014527324, -0.471746035838696, -1.40121013928348, 
    -0.340849646366211, 0.446634682274447, -0.0173418739290936
    ), v_ln_OR = c(0.357124952253629, 0.208132393657186, 0.43341307814992, 
    0.0203144129731974, 0.0519517773171203, 0.00990526551533824, 
    0.227009675223494, 0.00400696201214883, 0.0569771239877627, 
    0.0754217263149204, 0.0125251338202155, 0.534162172474717, 
    0.0716351172956587), ln_Odd_V = c(-3.39282913199164, -3.91202300542815, 
    -4.33073334028633, -5.38597369680091, -5.02785983369776, 
    -2.02301815176126, -5.75929601791945, -5.15923736981291, 
    -5.55135444814039, -4.60458177761572, -5.60295170807164, 
    -6.21180417108946, -6.43840328922512), ln_Odd_NV = c(-2.45413499112125, 
    -2.2458322764016, -2.94443897916644, -3.92953014748793, -4.80871874802232, 
    -1.06489611098499, -4.12552017969055, -5.17125797126564, 
    -5.07960841230169, -3.20337163833224, -5.26210206170543, 
    -6.6584388533639, -6.42106141529602), v_ln_Odd_V = c(0.258403361344538, 
    0.17, 0.337719298245614, 0.0162029093266224, 0.0305016005969143, 
    0.00629030941301331, 0.125394166338195, 0.00199157639633522, 
    0.0346166274292573, 0.059412110930305, 0.0053961664773948, 
    0.200401123144805, 0.0370962576932019), cov_V_NV = c(0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), v_ln_Odd_NV = c(0.0987215909090909, 
    0.038132393657186, 0.0956937799043062, 0.00411150364657493, 
    0.0214501767202059, 0.00361495610232493, 0.101615508885299, 
    0.00201538561581361, 0.0223604965585054, 0.0160096153846154, 
    0.00712896734282072, 0.333761049329912, 0.0345388596024568
    )), .Names = c("Trial", "Author", "Year", "VD", "VWD", "NVD", 
"NVWD", "Latitude", "Allocation", "ln_OR", "v_ln_OR", "ln_Odd_V", 
"ln_Odd_NV", "v_ln_Odd_V", "cov_V_NV", "v_ln_Odd_NV"), row.names = c(NA, 
-13L), class = "data.frame")