map_to_result: Map to results from data, variable names & case
In mabafaba/hypegrammaR: A grammar of hypothesis test driven analysis

Description Usage Arguments Details Value

Produce summary statistics, hypothesis tests and plot objects for a hypothesis

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map_to_result(data, dependent.var, independent.var = NULL, case,
  cluster.variable.name = NULL, weighting = function(df) {     rep(1,
  nrow(df)) }, questionnaire = NULL, confidence_level = 0.95)

`data`	the data as a data.frame. Must match the sampling frame used to produce the 'weighting' as well as the questionnaire if applicable.
`dependent.var`	string with the column name in "data" of the dependent variable
`case`	the analysis case, created with map_to_case().
`cluster.variable.name`	if cluster sampling, provide the name of the variable in the dataset that denotes the cluster
`weighting`	A function that generates weights from a dataframe. You can create it with surveyweights::weighting_fun_from_samplingframe()
`questionnaire`	output from load_questionnaire()
`confidence_level`	the confidence level to be used for confidence intervals (default: 0.95)
`independen.var`	string with the column name in 'data' of the independent variable

- takes as parameters outputs from - load_data() - map_to_case() - load_samplingframe() - load_questionnaire() - output can be processed by: - map_to_labeled() - map_to_visualisation() - map_to_table() - map_to_master_table() - map_to_visualisation_heatmap()

A list with the summary.statistic the hypothesis.test result

mabafaba/hypegrammaR documentation built on Oct. 2, 2019, 11:33 a.m.