I am using meta 4.9-5 package for conducting meta-analysis on correlation data. But I cannot figure out why it is unable to calculate lower and upper prediction intervals even I have set prediction = TRUE. Is it due to the small sample size (2 in the following sample code)? Any help is highly appreciated.
# Load required library library(meta) # Data to be processed D2P <- data.frame(stuid = c('S1','S2'), r = c(0.156, 0.117), n = c(559, 206)) # Conducting the meta analysis ma <- metacor(cor = r, data = D2P, n = n, studlab = stuid, prediction = T, level.predict = 0.9) # See the results > ma$prediction  TRUE > ma$lower.predict  NA > ma$upper.predict  NA > sessionInfo() R version 3.6.1 (2019-07-05) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows 10 x64 (build 18362) Matrix products: default locale:  LC_COLLATE=Chinese (Traditional)_Taiwan.950 LC_CTYPE=Chinese (Traditional)_Taiwan.950 LC_MONETARY=Chinese (Traditional)_Taiwan.950  LC_NUMERIC=C LC_TIME=Chinese (Traditional)_Taiwan.950 attached base packages:  stats graphics grDevices utils datasets methods base other attached packages:  dplyr_0.8.3 readxl_1.3.1 metafor_2.1-0 Matrix_1.2-17 meta_4.9-5 loaded via a namespace (and not attached):  Rcpp_1.0.1 lattice_0.20-38 crayon_1.3.4 assertthat_0.2.1 grid_3.6.1 cellranger_1.1.0 R6_2.4.0 nlme_3.1-140  magrittr_1.5 pillar_1.4.2 rlang_0.4.0 rstudioapi_0.10 tools_3.6.1 glue_1.3.1 purrr_0.3.2 compiler_3.6.1  pkgconfig_2.0.2 tidyselect_0.2.5 tibble_2.1.3