Calculate correlations for two or more variables
correlation( dataset, vars = "", method = "pearson", hcor = FALSE, hcor_se = FALSE, data_filter = "", envir = parent.frame() )
| dataset | Dataset |
|---|---|
| vars | Variables to include in the analysis. Default is all but character and factor variables with more than two unique values are removed |
| method | Type of correlations to calculate. Options are "pearson", "spearman", and "kendall". "pearson" is the default |
| hcor | Use polycor::hetcor to calculate the correlation matrix |
| hcor_se | Calculate standard errors when using polycor::hetcor |
| data_filter | Expression entered in, e.g., Data > View to filter the dataset in Radiant. The expression should be a string (e.g., "price > 10000") |
| envir | Environment to extract data from |
A list with all variables defined in the function as an object of class compare_means
See https://radiant-rstats.github.io/docs/basics/correlation.html for an example in Radiant
summary.correlation to summarize results
plot.correlation to plot results
#> List of 13 #> $ descr : chr "## Correlation matrix\n\nCorrelations were calculated using the \"diamonds\" dataset\n\nVariables used:\n\n* price\n* carat" #> $ adj_text : chr "\n\n" #> $ cvmat : num [1:2, 1:2] 1.57e+07 1.74e+03 1.74e+03 2.25e-01 #> ..- attr(*, "dimnames")=List of 2 #> .. ..$ : chr [1:2] "price" "carat" #> .. ..$ : chr [1:2] "price" "carat" #> $ cmat :List of 11 #> ..$ r : num [1:2, 1:2] 1 0.927 0.927 1 #> .. ..- attr(*, "dimnames")=List of 2 #> .. .. ..$ : chr [1:2] "price" "carat" #> .. .. ..$ : chr [1:2] "price" "carat" #> ..$ n : num 3000 #> ..$ t : num [1:2, 1:2] Inf 136 136 Inf #> .. ..- attr(*, "dimnames")=List of 2 #> .. .. ..$ : chr [1:2] "price" "carat" #> .. .. ..$ : chr [1:2] "price" "carat" #> ..$ p : num [1:2, 1:2] 0 0 0 0 #> .. ..- attr(*, "dimnames")=List of 2 #> .. .. ..$ : chr [1:2] "price" "carat" #> .. .. ..$ : chr [1:2] "price" "carat" #> ..$ se : num [1:2, 1:2] 0 0.00683 0.00683 0 #> .. ..- attr(*, "dimnames")=List of 2 #> .. .. ..$ : chr [1:2] "price" "carat" #> .. .. ..$ : chr [1:2] "price" "carat" #> ..$ sef : num 0.0183 #> ..$ adjust: chr "holm" #> ..$ sym : logi TRUE #> ..$ ci :'data.frame': 1 obs. of 4 variables: #> .. ..$ lower: num 0.922 #> .. ..$ r : num 0.927 #> .. ..$ upper: num 0.932 #> .. ..$ p : num 0 #> ..$ ci.adj:'data.frame': 1 obs. of 2 variables: #> .. ..$ lower.adj: num 0.922 #> .. ..$ upper.adj: num 0.932 #> ..$ Call : language psych::corr.test(x = num_dat, method = method) #> ..- attr(*, "class")= chr [1:2] "psych" "corr.test" #> $ not_vary : chr(0) #> $ anyCategorical: Named logi [1:2] FALSE FALSE #> ..- attr(*, "names")= chr [1:2] "price" "carat" #> $ df_name : chr "diamonds" #> $ dataset : tibble [3,000 × 2] (S3: tbl_df/tbl/data.frame) #> ..$ price: int [1:3000] 580 650 630 706 1080 3082 3328 4229 1895 3546 ... #> ..$ carat: num [1:3000] 0.32 0.34 0.3 0.35 0.4 0.6 0.88 0.93 0.51 1.01 ... #> ..- attr(*, "description")= chr "## Diamond prices\n\nPrices of 3,000 round cut diamonds\n\n### Description\n\nA dataset containing the prices a"| __truncated__ #> $ vars : chr [1:2] "price" "carat" #> $ method : chr "pearson" #> $ hcor : logi FALSE #> $ hcor_se : logi FALSE #> $ data_filter : chr "" #> - attr(*, "class")= chr [1:3] "rcorr" "correlation" "list"#> List of 13 #> $ descr : chr "## Correlation matrix\n\nCorrelations were calculated using the \"diamonds\" dataset\n\nVariables used:\n\n* x:z" #> $ adj_text : chr "\n\n" #> $ cvmat : num [1:3, 1:3] 1.263 1.251 0.773 1.251 1.242 ... #> ..- attr(*, "dimnames")=List of 2 #> .. ..$ : chr [1:3] "x" "y" "z" #> .. ..$ : chr [1:3] "x" "y" "z" #> $ cmat :List of 11 #> ..$ r : num [1:3, 1:3] 1 0.999 0.992 0.999 1 ... #> .. ..- attr(*, "dimnames")=List of 2 #> .. .. ..$ : chr [1:3] "x" "y" "z" #> .. .. ..$ : chr [1:3] "x" "y" "z" #> ..$ n : num 3000 #> ..$ t : num [1:3, 1:3] Inf 1107 422 1107 Inf ... #> .. ..- attr(*, "dimnames")=List of 2 #> .. .. ..$ : chr [1:3] "x" "y" "z" #> .. .. ..$ : chr [1:3] "x" "y" "z" #> ..$ p : num [1:3, 1:3] 0 0 0 0 0 0 0 0 0 #> .. ..- attr(*, "dimnames")=List of 2 #> .. .. ..$ : chr [1:3] "x" "y" "z" #> .. .. ..$ : chr [1:3] "x" "y" "z" #> ..$ se : num [1:3, 1:3] 0 0.000902 0.00235 0.000902 0 ... #> .. ..- attr(*, "dimnames")=List of 2 #> .. .. ..$ : chr [1:3] "x" "y" "z" #> .. .. ..$ : chr [1:3] "x" "y" "z" #> ..$ sef : num 0.0183 #> ..$ adjust: chr "holm" #> ..$ sym : logi TRUE #> ..$ ci :'data.frame': 3 obs. of 4 variables: #> .. ..$ lower: num [1:3] 0.999 0.991 0.991 #> .. ..$ r : num [1:3] 0.999 0.992 0.991 #> .. ..$ upper: num [1:3] 0.999 0.992 0.992 #> .. ..$ p : num [1:3] 0 0 0 #> ..$ ci.adj:'data.frame': 3 obs. of 2 variables: #> .. ..$ lower.adj: num [1:3] 0.999 0.991 0.991 #> .. ..$ upper.adj: num [1:3] 0.999 0.992 0.992 #> ..$ Call : language psych::corr.test(x = num_dat, method = method) #> ..- attr(*, "class")= chr [1:2] "psych" "corr.test" #> $ not_vary : chr(0) #> $ anyCategorical: Named logi [1:3] FALSE FALSE FALSE #> ..- attr(*, "names")= chr [1:3] "x" "y" "z" #> $ df_name : chr "diamonds" #> $ dataset : tibble [3,000 × 3] (S3: tbl_df/tbl/data.frame) #> ..$ x: num [1:3000] 4.43 4.45 4.27 4.6 4.72 5.35 6.14 6.34 5.09 6.31 ... #> ..$ y: num [1:3000] 4.45 4.42 4.23 4.65 4.68 5.43 6.18 6.23 5.06 6.37 ... #> ..$ z: num [1:3000] 2.71 2.81 2.68 2.74 2.94 3.38 3.8 3.86 3.22 4.05 ... #> ..- attr(*, "description")= chr "## Diamond prices\n\nPrices of 3,000 round cut diamonds\n\n### Description\n\nA dataset containing the prices a"| __truncated__ #> $ vars : chr "x:z" #> $ method : chr "pearson" #> $ hcor : logi FALSE #> $ hcor_se : logi FALSE #> $ data_filter : chr "" #> - attr(*, "class")= chr [1:3] "rcorr" "correlation" "list"