Upgrade a dataframe to an mxData type.
xmu_make_mxData is an internal function to upgrade a dataframe to mxData. It can also drop variables and rows
from the dataframe.
The most common use will be to give it a dataframe, and get back an mxData object of type raw, cov, cor (WLS is just raw).
xmu_make_mxData(
data = NULL,
type = c("Auto", "FIML", "cov", "cor", "WLS", "DWLS", "ULS"),
manifests = NULL,
numObs = NULL,
fullCovs = NULL,
dropMissingDef = TRUE,
verbose = FALSE,
use = "pairwise.complete.obs"
)data |
A |
type |
What data type is wanted out c("Auto", "FIML", "cov", "cor", 'WLS', 'DWLS', 'ULS') |
manifests |
If set, only these variables will be retained. |
numObs |
Only needed if you pass in a cov/cor matrix wanting this to be upgraded to mxData |
fullCovs |
Covariate names if any (NULL = none) These are checked by |
dropMissingDef |
Whether to automatically drop missing def var rows for the user (default = TRUE). You get a polite note. |
verbose |
If verbose, report on columns kept and dropped (default FALSE) |
use |
When type = cov or cor, should this drop NAs? (use = "pairwise.complete.obs" by default, with a polite note) |
Other xmu internal not for end user:
umxModel(),
umxRenameMatrix(),
umx_APA_pval(),
umx_fun_mean_sd(),
umx_get_bracket_addresses(),
umx_make(),
umx_standardize(),
umx_string_to_algebra(),
umx,
xmuHasSquareBrackets(),
xmuLabel_MATRIX_Model(),
xmuLabel_Matrix(),
xmuLabel_RAM_Model(),
xmuMI(),
xmuMakeDeviationThresholdsMatrices(),
xmuMakeOneHeadedPathsFromPathList(),
xmuMakeTwoHeadedPathsFromPathList(),
xmuMaxLevels(),
xmuMinLevels(),
xmuPropagateLabels(),
xmuRAM2Ordinal(),
xmuTwinSuper_Continuous(),
xmuTwinSuper_NoBinary(),
xmuTwinUpgradeMeansToCovariateModel(),
xmu_CI_merge(),
xmu_CI_stash(),
xmu_DF_to_mxData_TypeCov(),
xmu_PadAndPruneForDefVars(),
xmu_bracket_address2rclabel(),
xmu_cell_is_on(),
xmu_check_levels_identical(),
xmu_check_needs_means(),
xmu_check_variance(),
xmu_clean_label(),
xmu_data_missing(),
xmu_data_swap_a_block(),
xmu_describe_data_WLS(),
xmu_dot_make_paths(),
xmu_dot_make_residuals(),
xmu_dot_maker(),
xmu_dot_move_ranks(),
xmu_dot_rank_str(),
xmu_extract_column(),
xmu_get_CI(),
xmu_lavaan_process_group(),
xmu_make_TwinSuperModel(),
xmu_make_bin_cont_pair_data(),
xmu_match.arg(),
xmu_name_from_lavaan_str(),
xmu_path2twin(),
xmu_path_regex(),
xmu_print_algebras(),
xmu_rclabel_2_bracket_address(),
xmu_safe_run_summary(),
xmu_set_sep_from_suffix(),
xmu_show_fit_or_comparison(),
xmu_simplex_corner(),
xmu_standardize_ACEcov(),
xmu_standardize_ACEv(),
xmu_standardize_ACE(),
xmu_standardize_CP(),
xmu_standardize_IP(),
xmu_standardize_RAM(),
xmu_standardize_SexLim(),
xmu_standardize_Simplex(),
xmu_start_value_list(),
xmu_starts(),
xmu_summary_RAM_group_parameters(),
xmu_twin_add_WeightMatrices(),
xmu_twin_check(),
xmu_twin_get_var_names(),
xmu_twin_make_def_means_mats_and_alg(),
xmu_twin_upgrade_selDvs2SelVars()
# =========================
# = Continuous ML example =
# =========================
data(mtcars)
tmp = xmu_make_mxData(data= mtcars, type = "Auto"); # class(tmp); # "MxDataStatic"
# names(tmp$observed) # "mpg" "cyl" "disp"
manVars = c("mpg", "cyl", "disp")
tmp = xmu_make_mxData(data= mtcars, type = "Auto", manifests = manVars);
tmp$type == "raw" # TRUE
# ==============================
# = All continuous WLS example =
# ==============================
tmp = xmu_make_mxData(data= mtcars, type = "WLS" , manifests = manVars, verbose= TRUE)
tmp$type == "raw" # TRUE (WLS is triggered by the fit function, not the data type)
# ============================
# = Missing data WLS example =
# ============================
tmp = mtcars; tmp[1, "mpg"] = NA # add NA
tmp = xmu_make_mxData(data= tmp, type = "WLS", manifests = manVars, verbose= TRUE)
# ==========================
# = already mxData example =
# ==========================
m1 = umxRAM("auto", data = mxData(mtcars, type = "raw"),
umxPath(var= "wt"),
umxPath(mean= "wt")
)
# ========================
# = Cov and cor examples =
# ========================
tmp = xmu_make_mxData(data= mtcars, type = "cov", manifests = c("mpg", "cyl"))
tmp = xmu_make_mxData(data= mtcars, type = "cor", manifests = c("mpg", "cyl"))
tmp = xmu_make_mxData(data= cov(mtcars[, c("mpg", "cyl")]),
type = "cov", manifests = c("mpg", "cyl"), numObs=200)
# mxData input examples
tmp = mxData(cov(mtcars[, c("mpg", "cyl")]), type = "cov", numObs= 100)
xmu_make_mxData(data= tmp, type = "cor", manifests = c("mpg", "cyl")) # consume mxData
xmu_make_mxData(data= tmp, type = "cor", manifests = c("mpg")) # trim existing mxData
xmu_make_mxData(data= tmp, type = "cor") # no manifests specified (use all)
xmu_make_mxData(data= tmp, manifests = c("mpg", "cyl")) # auto
# =======================
# = Pass string through =
# =======================
xmu_make_mxData(data= c("a", "b", "c"), type = "Auto")Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.