1000 rows from th 2018 CCES Common Content. Contains all columns, retaining the haven_labelled class. This is doi:10.7910/DVN/ZSBZ7K/H5IDTA originally read in using read_dta via get_cces_dataverse(). To search for variable by its content, questionr::lookfor (or rcces::vartab) is a useful option (see example).

cc18_samp

Format

An object of class tbl_df (inherits from tbl, data.frame) with 1000 rows and 526 columns.

Source

"Brian Schaffner; Stephen Ansolabehere; Sam Luks, 2019, "CCES Common Content, 2018", doi:https://doi.org/10.7910, Harvard Dataverse V6.

Details

See the 2018 Codebook in the DOI below for question wording of each column. To use the harmonized and easier-to-use versions of common variables like geography, partisan ID, demographics and vote choice, use the cumulative common content, of which 2018 is a subset. A sample of the cumulative is contained in this package as ?ccc_samp.

Examples

# use questionr::lookfor to search the label and labels questionr::lookfor(cc18_samp, "Trump")
#> pos variable label col_type values #> 91 CC18_308a Job approval -- Pres~ dbl+lbl [1] Strongly approve #> [2] Somewhat approve #> [3] Somewhat disappr~ #> [4] Strongly disappr~ #> [5] Not sure #> [8] skipped #> [9] not asked #> 149 CC18_334C Ideological Placemen~ dbl+lbl [1] Very Liberal #> [2] Liberal #> [3] Somewhat Liberal #> [4] Middle of the Ro~ #> [5] Somewhat Conserv~ #> [6] Conservative #> [7] Very Conservative #> [8] Not sure #> [98] skipped #> [99] not asked #> 162 CC18_335 Trump Russia collusi~ dbl+lbl [1] Yes #> [2] No #> [3] Not sure #> [8] skipped #> [9] not asked #> 430 CC18_app_dtrmp_post President Trump Job ~ dbl+lbl [1] Strongly approve #> [2] Somewhat approve #> [3] Somewhat disappr~ #> [4] Strongly disappr~ #> [5] Not sure #> [8] skipped #> [9] not asked
# all data cc18_samp
#> # A tibble: 1,000 × 526 #> year case_id commonweight commonpostweight vvweight vvweight_post tookpost #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl+lb> #> 1 2018 415395741 1.47 1.48 NA NA 2 [Yes] #> 2 2018 414164923 1.33 1.22 1.51 1.29 2 [Yes] #> 3 2018 412379892 0.641 0.559 0.602 0.594 2 [Yes] #> 4 2018 414203529 1.35 1.19 1.18 1.17 2 [Yes] #> 5 2018 412148048 0.870 0.762 0.842 0.742 2 [Yes] #> 6 2018 412329835 0.949 0.789 1.07 0.983 2 [Yes] #> 7 2018 417352072 0.688 0.585 0.717 0.716 2 [Yes] #> 8 2018 414614677 0.814 0.616 NA NA 2 [Yes] #> 9 2018 416797006 1.12 0.926 0.991 0.929 2 [Yes] #> 10 2018 412962561 1.05 0.877 0.346 0.372 2 [Yes] #> # … with 990 more rows, and 519 more variables: CCEStake <dbl+lbl>, #> # birthyr <dbl>, gender <dbl+lbl>, educ <dbl+lbl>, race <dbl+lbl>, #> # race_other <chr>, hispanic <dbl+lbl>, marstat <dbl+lbl>, #> # multrace_1 <dbl+lbl>, multrace_2 <dbl+lbl>, multrace_3 <dbl+lbl>, #> # multrace_4 <dbl+lbl>, multrace_5 <dbl+lbl>, multrace_8 <dbl+lbl>, #> # multrace_97 <dbl+lbl>, multrace_98 <dbl+lbl>, multrace_99 <dbl+lbl>, #> # CC18_354a_1 <dbl+lbl>, CC18_354a_2 <dbl+lbl>, CC18_354a_3 <dbl+lbl>, …