Specify response and explanatory variables

specify() is used to specify which columns in the supplied data frame are the relevant response (and, if applicable, explanatory) variables. Note that character variables are converted to factors.

Learn more in vignette("infer").

specify(x, formula, response = NULL, explanatory = NULL, success = NULL)

Arguments

x	A data frame that can be coerced into a tibble.
formula	A formula with the response variable on the left and the explanatory on the right. Alternatively, a response and explanatory argument can be supplied.
response	The variable name in x that will serve as the response. This is an alternative to using the formula argument.
explanatory	The variable name in x that will serve as the explanatory variable. This is an alternative to using the formula argument.
success	The level of response that will be considered a success, as a string. Needed for inference on one proportion, a difference in proportions, and corresponding z stats.

Value

A tibble containing the response (and explanatory, if specified) variable data.

See also

Other core functions: calculate(), generate(), hypothesize()

Examples

# specifying for a point estimate on one variable
gss %>%
   specify(response = age)
#> Response: age (numeric)
#> # A tibble: 500 × 1
#>      age
#>    <dbl>
#>  1    36
#>  2    34
#>  3    24
#>  4    42
#>  5    31
#>  6    32
#>  7    48
#>  8    36
#>  9    30
#> 10    33
#> # … with 490 more rows

# specify a relationship between variables as a formula...
gss %>%
  specify(age ~ partyid)
#> Dropping unused factor levels DK from the supplied explanatory variable 'partyid'.
#> Response: age (numeric)
#> Explanatory: partyid (factor)
#> # A tibble: 500 × 2
#>      age partyid
#>    <dbl> <fct>  
#>  1    36 ind    
#>  2    34 rep    
#>  3    24 ind    
#>  4    42 ind    
#>  5    31 rep    
#>  6    32 rep    
#>  7    48 dem    
#>  8    36 ind    
#>  9    30 rep    
#> 10    33 dem    
#> # … with 490 more rows
  
# ...or with named arguments!
gss %>%
  specify(response = age, explanatory = partyid)
#> Dropping unused factor levels DK from the supplied explanatory variable 'partyid'.
#> Response: age (numeric)
#> Explanatory: partyid (factor)
#> # A tibble: 500 × 2
#>      age partyid
#>    <dbl> <fct>  
#>  1    36 ind    
#>  2    34 rep    
#>  3    24 ind    
#>  4    42 ind    
#>  5    31 rep    
#>  6    32 rep    
#>  7    48 dem    
#>  8    36 ind    
#>  9    30 rep    
#> 10    33 dem    
#> # … with 490 more rows

# more in-depth explanation of how to use the infer package
if (FALSE) {
vignette("infer")
}