Estimate Means of Mobility Survey

mzmv_mean() estimates the means, proportions and confidence intervals of FSO mobility surveys.

Usage

mzmv_mean(data, ..., weight, cf = 1.14, alpha = 0.1)

Arguments

data

A data frame or tibble.

...

Names of variables to be estimated. Can be passed unquoted (e.g., household_size) or programmatically using !!!syms(c("annual_household_income", "household_size")). Variables have integer values, representing a quantity (number of cars per household) or presence/absence (possession of a car). Negative numbers represent NA.

weight

Unquoted or quoted name of the sampling weights column. For programmatic use with a string variable (e.g., wt <- "weights"), use !!sym(wt) in the function call.

cf

Numeric correction factor of the confidence interval, supplied by FSO. Default is 1.14.

alpha

Numeric significance level for confidence intervals. Default is 0.1 (90% CI).

Value

Tibble (number of rows is length of variable) with the following columns:

• id: estimated item

• occ: number of survey responses

• wmean: weighted mean estimate

• ci: confidence interval estimate

See also

See mzmv_mean_map for estimates on a set of conditions.

Examples

# Estimate two means
mzmv_mean(
  data = nhanes,
  annual_household_income, annual_family_income,
  weight = weights
)
#> # A tibble: 2 × 4
#>   variable                  occ wmean    ci
#>   <chr>                   <int> <dbl> <dbl>
#> 1 annual_household_income  9626  11.9 0.240
#> 2 annual_family_income     9642  11.5 0.245
# Programmatic use with strings
v <- c("annual_household_income", "annual_family_income")
mzmv_mean(nhanes, weight = "weights", !!!rlang::syms(v))
#> # A tibble: 2 × 4
#>   variable                  occ wmean    ci
#>   <chr>                   <int> <dbl> <dbl>
#> 1 annual_household_income  9626  11.9 0.240
#> 2 annual_family_income     9642  11.5 0.245