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Tidycomm provides a workflow to quickly add mean/sum indices of several variables to the dataset and compute reliability estimates for those added indices:
add_index() adds a mean or sum index of the specified
variablesget_reliability() computes reliability estimates for
all added indicesOnce again, we will again sample data from the Worlds of Journalism 2012-16 study for demonstration purposes.
WoJ
#> # A tibble: 1,200 × 15
#> country reach employment temp_contract autonomy_selection autonomy_emphasis
#> <fct> <fct> <chr> <fct> <dbl> <dbl>
#> 1 Germany Nati… Full-time Permanent 5 4
#> 2 Germany Nati… Full-time Permanent 3 4
#> 3 Switzerl… Regi… Full-time Permanent 4 4
#> 4 Switzerl… Local Part-time Permanent 4 5
#> 5 Austria Nati… Part-time Permanent 4 4
#> 6 Switzerl… Local Freelancer <NA> 4 4
#> 7 Germany Local Full-time Permanent 4 4
#> 8 Denmark Nati… Full-time Permanent 3 3
#> 9 Switzerl… Local Full-time Permanent 5 5
#> 10 Denmark Nati… Full-time Permanent 2 4
#> # ℹ 1,190 more rows
#> # ℹ 9 more variables: ethics_1 <dbl>, ethics_2 <dbl>, ethics_3 <dbl>,
#> # ethics_4 <dbl>, work_experience <dbl>, trust_parliament <dbl>,
#> # trust_government <dbl>, trust_parties <dbl>, trust_politicians <dbl>ethics_1 to ethics_4 measure agreement with
statements concerning ethics in journalism and may be combined into an
index of ‘ethical flexbility’, while the items starting with
trust_ measure trust in various political institutions and
thus may be combined into an index of trust in politics.
add_index() adds a mean index of specified variables to
the data. The second (or first, if used in a pipe) argument is the name
of index variable to be created:
WoJ %>%
add_index(ethical_flexibility, ethics_1, ethics_2, ethics_3, ethics_4) %>%
# Select variables of relevance for output
dplyr::select(ethical_flexibility, ethics_1, ethics_2, ethics_3, ethics_4)
#> # A tibble: 1,200 × 5
#> ethical_flexibility ethics_1 ethics_2 ethics_3 ethics_4
#> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 2 2 3 2 1
#> 2 1.5 1 2 2 1
#> 3 2.25 2 4 2 1
#> 4 1.75 1 3 1 2
#> 5 2 2 3 2 1
#> 6 3.25 2 4 4 3
#> 7 2 1 3 2 2
#> 8 3.5 2 4 4 4
#> 9 1.75 1 2 1 3
#> 10 3.25 1 4 4 4
#> # ℹ 1,190 more rowsTo create a sum index instead, set type = "sum":
WoJ %>%
add_index(ethical_flexibility, ethics_1, ethics_2, ethics_3, ethics_4, type = "sum") %>%
# Select variables of relevance for output
dplyr::select(ethical_flexibility, ethics_1, ethics_2, ethics_3, ethics_4)
#> # A tibble: 1,200 × 5
#> ethical_flexibility ethics_1 ethics_2 ethics_3 ethics_4
#> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 8 2 3 2 1
#> 2 6 1 2 2 1
#> 3 9 2 4 2 1
#> 4 7 1 3 1 2
#> 5 8 2 3 2 1
#> 6 13 2 4 4 3
#> 7 8 1 3 2 2
#> 8 14 2 4 4 4
#> 9 7 1 2 1 3
#> 10 13 1 4 4 4
#> # ℹ 1,190 more rowsUse get_reliability() to compute reliability/internal
consistency estimates for indices created with add_index().
Passing no further arguments to the function will automatically compute
reliability estimates for all indices created with
add_index() found in the data and output Cronbach’s \(\alpha\) along with descriptives and index
information.
# Add two indices to data
WoJ <- WoJ %>%
add_index(ethical_flexibility, ethics_1, ethics_2, ethics_3, ethics_4) %>%
add_index(trust_in_politics, trust_parliament, trust_government, trust_parties, trust_politicians)
WoJ %>%
get_reliability()
#> # A tibble: 2 × 5
#> Index Index_of M SD Cronbachs_Alpha
#> * <chr> <chr> <dbl> <dbl> <dbl>
#> 1 ethical_flexibility ethics_1, ethics_2, ethics_3,… 2.45 0.777 0.612
#> 2 trust_in_politics trust_parliament, trust_gover… 2.70 0.652 0.856If you only want reliability estimates for specific indices, pass their names as function arguments.
WoJ %>%
get_reliability(trust_in_politics)
#> # A tibble: 1 × 5
#> Index Index_of M SD Cronbachs_Alpha
#> * <chr> <chr> <dbl> <dbl> <dbl>
#> 1 trust_in_politics trust_parliament, trust_governm… 2.70 0.652 0.856Essentially, get_reliability() provides a wrapper for the ci.reliability
function from the MBESS package. Thus, all arguments of
MBESS::ci.reliability() can be passed to
get_reliability(). For example, to output \(\omega\) instead of Cronbach’s \(\alpha\) including robust maximum
likelihood confidence intervals, you can type:
WoJ %>%
get_reliability(type = 'omega', interval.type = 'mlr')
#> # A tibble: 2 × 8
#> Index Index_of M SD Omega CI_LL CI_UL CI_Type
#> * <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <chr>
#> 1 ethical_flexibility ethics_1, ethics_2,… 2.45 0.777 0.626 0.590 0.663 robust…
#> 2 trust_in_politics trust_parliament, t… 2.70 0.652 0.856 0.840 0.871 robust…See the function
documentation for more info (and don’t forget to cite the
MBESS package if using get_reliability()).
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.