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| sjmisc-package | Data Transformation and Labelled Data Utility Functions |
| add_labels | Add value labels to variables |
| add_labels<- | Add value labels to variables |
| as_labelled | Convert vector to labelled class |
| chisq_gof | Chi-square goodness-of-fit-test |
| cod | Tjur's Coefficient of Discrimination |
| converge_ok | Convergence test for mixed effects models |
| copy_labels | Copy value and variable labels to (subsetted) data frames |
| cramer | Cramer's V for a contingency table |
| cronb | Cronbach's Alpha for a matrix or data frame |
| cv | Coefficient of Variation |
| deff | Design effects for two-level mixed models |
| dicho | Dichotomize variables |
| drop_labels | Drop labels of zero-count values |
| efc | Sample dataset from the EUROFAMCARE project |
| eta_sq | Eta-squared of fitted anova |
| fill_labels | Add missing value labels to partially labelled vector |
| frq | Summary of labelled vectors |
| get_frq | Get summary of labelled vectors |
| get_label | Retrieve variable label(s) of labelled data |
| get_labels | Retrieve value labels of labelled data |
| get_na | Retrieve missing values of labelled variables |
| get_na_flags | Retrieve missing value flags of labelled variables |
| get_note | Retrieve notes (annotations) from labelled variables |
| get_re_var | Random effect variances |
| get_values | Retrieve values of labelled variables |
| group_labels | Create labels for recoded groups |
| group_str | Group near elements of string vectors |
| group_var | Recode numeric variables into equal-ranged groups |
| hoslem_gof | Hosmer-Lemeshow Goodness-of-fit-test |
| icc | Intraclass-Correlation Coefficient |
| is_crossed | Check whether two factors are crossed |
| is_empty | Check whether string or vector is empty |
| is_even | Check whether value is even |
| is_labelled | Check whether object is of class "labelled" |
| is_nested | Check whether two factors are nested |
| is_num_fac | Check whether a factor has numeric levels only |
| is_odd | Check whether value is odd |
| labelled | Create a labelled vector |
| lbl_df | Create a labelled data frame |
| levene_test | Plot Levene-Test for One-Way-Anova |
| mean_n | Row means with min amount of valid values |
| merge_df | Merge labelled data frames |
| mic | Mean Inter-Item-Correlation |
| mwu | Mann-Whitney-U-Test |
| overdisp | Check overdispersion of GL(M)M's |
| phi | Phi value for contingency tables |
| r2 | Compute R-squared of (generalized) linear (mixed) models |
| read_sas | Import SAS dataset as data frame into R |
| read_spss | Import SPSS dataset as data frame into R |
| read_stata | Import STATA dataset as data frame into R |
| rec | Recode variables |
| rec<- | Recode variables |
| recode_to | Recode variable categories into new values |
| rec_pattern | Create recode pattern for 'rec' function |
| ref_lvl | Change reference level of (numeric) factors |
| ref_lvl<- | Change reference level of (numeric) factors |
| reliab_test | Performs a reliability test on an item scale |
| remove_all_labels | Remove value and variable labels from vector or data frame |
| remove_labels | Remove value labels from variables |
| remove_labels<- | Remove value labels from variables |
| replace_na | Replace NA with specific values |
| replace_na<- | Replace NA with specific values |
| re_var | Random effect variances |
| rmse | Root Mean Squared Error (RMSE) |
| se | Standard Error for variables |
| set_label | Add variable label(s) to variables |
| set_label<- | Add variable label(s) to variables |
| set_labels | Add value labels to variables |
| set_labels<- | Add value labels to variables |
| set_na | Set NA for specific variable values |
| set_na<- | Set NA for specific variable values |
| set_note | Add notes (annotations) to (labelled) variables |
| set_note<- | Add notes (annotations) to (labelled) variables |
| sjmisc | Data Transformation and Labelled Data Utility Functions |
| smpsize_lmm | Sample size for linear mixed models |
| split_var | Split numeric variables into smaller groups |
| std_beta | Standardized Beta coefficients and CI of lm and mixed models |
| str_contains | Check if string contains pattern |
| str_pos | Find partial matching and close distance elements in strings |
| table_values | Expected and relative table values |
| to_dummy | Split (categorical) vectors into dummy variables |
| to_factor | Convert variable into factor and keep value labels |
| to_label | Convert variable into factor and replaces values with associated value labels |
| to_long | Convert wide data to long format |
| to_na | Convert missing values of labelled variables into NA |
| to_value | Convert factors to numeric variables |
| trim | Trim leading and trailing whitespaces from strings |
| unlabel | Convert labelled vectors into normal classes |
| weight | Weight a variable |
| weight2 | Weight a variable |
| word_wrap | Insert line breaks in long labels |
| write_spss | Write content of data frame to SPSS sav-file |
| write_stata | Write content of data frame to STATA dta-file |
| wtd_sd | Weighted standard deviation for variables |
| wtd_se | Weighted standard error for variables |
| zap_labels | Convert labelled values into NA |
| zap_unlabelled | Convert non-labelled values into NA |