get.analyses: get.analyses
In ManyLabsOpenScience/manylabRs: Analysis scripts and data from the Many Labs projects

Description Usage Arguments Details Value See Also Examples

get.analyses

get.analyses(studies = NA, analysis.type = NA, Nmin.raw = 30,
  Nmin.cond = 15, subset = c("all", "WEIRD", "NONWEIRD")[1],
  onlineTables = TRUE, staticData = TRUE, saveRdata = FALSE,
  rootdir = normalizePath(paste0(find.package("manylabRs"))),
  indir = list(RAW_DATA = ifelse(staticData, file.path(rootdir, "extdata",
  "RAW_DATA"), ""), MASTERKEY = ifelse(onlineTables, "", file.path(rootdir,
  "extdata", "KEYTABLES")), SOURCE_INFO = ifelse(onlineTables, "",
  file.path(rootdir, "extdata", "KEYTABLES"))), outdir = list(R_OBJECTS =
  ifelse(saveRdata, file.path(rootdir, "extdata", "R_OBJECTS"), ""), RDS_RESULTS
  = ifelse(saveRdata, file.path(rootdir, "extdata", "RESULTS_RDS"), "")),
  data.names = list(Slate1 = ifelse(staticData, file.path(rootdir, "extdata",
  "RAW_DATA", "ML2_Rawdata_S1.RData"), "ML2_S1"), Slate2 = ifelse(staticData,
  file.path(rootdir, "extdata", "RAW_DATA", "ML2_Rawdata_S2.RData"), "ML2_S2")))

get.analyses(studies = NA, analysis.type = NA, Nmin.raw = 30,
  Nmin.cond = 15, subset = c("all", "WEIRD", "NONWEIRD")[1],
  onlineTables = TRUE, staticData = TRUE, saveRdata = FALSE,
  rootdir = normalizePath(paste0(find.package("manylabRs"))),
  indir = list(RAW_DATA = ifelse(staticData, file.path(rootdir, "extdata",
  "RAW_DATA"), ""), MASTERKEY = ifelse(onlineTables, "", file.path(rootdir,
  "extdata", "KEYTABLES")), SOURCE_INFO = ifelse(onlineTables, "",
  file.path(rootdir, "extdata", "KEYTABLES"))), outdir = list(R_OBJECTS =
  ifelse(saveRdata, file.path(rootdir, "extdata", "R_OBJECTS"), ""), RDS_RESULTS
  = ifelse(saveRdata, file.path(rootdir, "extdata", "RESULTS_RDS"), "")),
  data.names = list(Slate1 = ifelse(staticData, file.path(rootdir, "extdata",
  "RAW_DATA", "ML2_Rawdata_S1.RData"), "ML2_S1"), Slate2 = ifelse(staticData,
  file.path(rootdir, "extdata", "RAW_DATA", "ML2_Rawdata_S2.RData"), "ML2_S2")))

`studies`	Numeric vector with unique study IDs listed in the 'masteRkey' table (default = all IDs).
`analysis.type`	An optional number indicating Global (1), Primary (2, default) or Secondary (3) analyses.
`Nmin.raw`	Minimum raw sample size allowed to be included in the analyses.
`Nmin.cond`	Minimum sample size per condition allowed to be included in the analyses.
`subset`	Can be "all","WEIRD" or "NONWEIRD"
`onlineTables`	Download most recent online versions of `masteRkey` and `Source` information.
`staticData`	Use data from external directory (see argument `indir`)
`saveRdata`	Save data in 'R' format. If 'TRUE' a list object is expected with two fieldnames: 'R_OBJECTS' and 'RDS_RESULTS', one for storing a seperate Robject for each analysis conducted, the other for storing a single data image containing the output returned by the function. An empty character vector will prevent saving any objects
`rootdir`	which dir to look for data and files
`indir`	List of directories to use for different files. Change if you have files in different locations, but keep the list structure!
`outdir`	List of directories to use for outputting different result files. Change if you want to save in a different location, but keep the list structure!
`data.names`	names of the datafiles for slate 1 and slate 2 (change e.g. if you study a custom subsample)
`studies`	Numeric vector with unique study IDs listed in the 'masteRkey' table (default = all IDs).
`analysis.type`	An optional number indicating Global (1), Primary (2, default) or Secondary (3) analyses.
`Nmin.raw`	Minimum raw sample size allowed to be included in the analyses.
`Nmin.cond`	Minimum sample size per condition allowed to be included in the analyses.
`subset`	Can be "all","WEIRD" or "NONWEIRD"
`onlineTables`	Download most recent online versions of `masteRkey` and `Source` information.
`staticData`	Use data from external directory (see argument `indir`)
`saveRdata`	Save data in 'R' format. If 'TRUE' a list object is expected with two fieldnames: 'R_OBJECTS' and 'RDS_RESULTS', one for storing a seperate Robject for each analysis conducted, the other for storing a single data image containing the output returned by the function. An empty character vector will prevent saving any objects
`rootdir`	which dir to look for data and files
`data.names`	names of the datafiles for slate 1 and slate 2 (change e.g. if you study a custom subsample)
`indir`	List of directories to use for different files. Change if you have files in different locations, but keep the list structure!
`outdir`	List of directories to use for outputting different result files. Change if you want to save in a different location, but keep the list structure!

Run analyses for (selected) ML2 studies.

A list object with analysis results.

Other "get." functions: get.GoogleSheet, get.OSFfile, get.Order, get.zavCode

# Get the data from analysis 1 [Huang.1] listed on the \href{masteRkey spreadsheet}{https://docs.google.com/spreadsheets/d/1fqK3WHwFPMIjNVVvmxpMEjzUETftq_DmP5LzEhXxUHA/}

library(dplyr)
df <- get.analyses(studies = 1, analysis.type = 1)

# 'raw' pre-filter dataset
head(tbl_df(df$raw.case$Huang.1))

# analysis results
glimpse(tbl_df(df$merged.results$Huang.1))

# Get the data from analysis 1 [Huang.1] listed on the \href{masteRkey spreadsheet}{https://docs.google.com/spreadsheets/d/1fqK3WHwFPMIjNVVvmxpMEjzUETftq_DmP5LzEhXxUHA/}

library(dplyr)
df <- get.analyses(studies = 1, analysis.type = 1)

# 'raw' pre-filter dataset
head(tbl_df(df$raw.case$Huang.1))

# analysis results
glimpse(tbl_df(df$merged.results$Huang.1))