Version 2.0.0
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General:
* sjmisc now supports tagged NA values, a new structure for labelled missing values introduced by the haven-package. This means that functions or arguments that are no longer useful, have been removed while other functions dealing with NA values have been largely revised.
* All statistical functions have been removed and are now in a separate package, `sjstats` (https://cran.r-project.org/package=sjstats).
* Removed some S3-methods for `labelled`-class, as these are now provided by the haven-package.
* Functions no longer check input for type `matrix`, to avoid conflicts with scaled vectors (that were recognized as matrix and hence treated as data frame).
* `table(*, exclude = NULL)` was changed to `table(*, useNA = "always")`, because of planned changes in upcoming R version 3.4.
* More functions (like `trim()` or `frq()`) now also have data frame- or list-methods.

New functions:
* `zap_na_tags()` to turn tagged NA values into regular NA values.
* `spread_coef()` to spread coefficients of multiple fitted models in nested data frames into columns.
* `merge_imputations()` to find the most likely imputed value for a missing value.
* `flat_table()` to print flat (proportional) tables of labelled variables.
* Added `to_character()` method.
* `big_mark()` to format large numbers with big marks.
* `empty_cols()` and `empty_rows()` to find variables or observations with exclusively NA values in a data frame.
* `remove_empty_cols()` and `remove_empty_rows()` to remove variables or observations with exclusively NA values from a data frame.

Changes to functions:
* `str_contains()` gets a `switch` argument to switch the role of `x` and `pattern`.
* `word_wrap()` coerces vectors to character if necessary.
* `to_label()` gets a `var.label` and `drop.levels` argument, and now preserves variable labels by default.
* Argument `def.value` in `get_label()` now also applies to data frame arguments.
* If factor levels are numeric and factor has value labels, these are used in `to_value()` by default.
* `to_factor()` no longer generates `NA` or `NaN`-levels when converting input into factors.

Bug fixes:
* `rec()` did not recode values, when these were the first element of a multi-line string of the `recodes` argument.
* `is_empty()` returned `NA` instead of `TRUE` for empty character vectors.
* Fixed bug with erroneous assignment of value labels to subset data when using `copy_labels()`.


Version 1.8
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New functions:
* `smpsize_lmm()` to compute approximated sample size for two-level linear mixed models.
* `deff()` to compute the design effect for two-level linear mixed models.
* `get_re_var()` to get specific components of the random effect variances from mixed models.

Changes to functions:
* `to_long()` can now also gather columns according to their column numbers.
* `merge_df()` now optionally merges more than two data frames at once.
* `frq()` and `get_frq()` now also return frequencies (counts) of character vectors.
* `rec()` now also works for character vectors and non-numeric factors.
* `set_labels()` now also works for character vectors.
* `drop_labels()` now also works for character vectors.
* `to_value()` now keeps labels of character vectors.
* `to_label()` now also works for character vectors and non-numeric factors.
* `mwu()` now also works when `grp` is a character vector.
* Generally, a better support for character vectors in label functions.
* Argument `enc` now also applies to `read_spss()` for haven-option.

Bug fixes:
* `merge_df()` did not copy all variable and value labels from second data frame.
* `merge_df()` did not work when data frames had no matching columns.
* `std_beta()` did not work when fitted model had no intercept.
* `set_labels()` now also works correctly for ordered factors.


Version 1.7
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General:
* Package is now depending on R >= 3.2, because some macros for RD-files did not work on older R-releases.

New functions:
* `merge_df()` to fully join labelled data frame and preserve value and variable labels.
* `wtd_sd()` to compute weighted standard deviations.
* `wtd_se()` to compute weighted standard errors.
* `get_note()` and `set_note()` to annotate vectors.
* `re_var()` to print random effect variances of `merMod`-objects. This function is just a convenient wrapper for `print.icc.lme4()` with `comp`-argument.
* `print.labelled()` generic method for printing labelled class vectors. Unlike 'haven's print-method, this method also prints variable labels and, if available, vector annotations and missing value attributes.
* S3-method `model.frame.gls()`.

Changes to functions:
* `icc()` now also returns variance parameters of random effects as attributes.
* `print.icc.lme4()` gets a `comp`-argument to also print variance parameters (see `?icc` for details).
* `r2()` also computes pseudo-R2 based on random effect variances.
* S3-method `mean.labelled()` only prints a message instead of warning, when `x` has labelled missing values.


Version 1.6
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New functions:
* `rec_pattern()` to generate recode patterns for the `rec()` function.
* `drop_labels()` to drop labels from values with zero-counts.
* `str_contains()` to check whether a string contains another string pattern.
* `r2()` to compute R-squared values for linear (mixed) models.
* `lbl_df()` to create a labelled data frame, and related S3-generic print method for `lbl_df` objects.

Changes to functions:
* `cv()` now accepts multiple arguments.
* `icc()` now accepts multiple arguments.
* `weight()` now also weights character vectors.
* `overdisp()` now wraps `AER::dispersiontest` to also support simple glm's.
* Removed deprecated functions.

Bug fixes:
* Fixed bug in `ref_lvl()`, where value labels were not correctly re-ordered for factors that had a `0` as level.
* Fixed bug in `rec()`, where value labels were not automatically re-ordered when `x` was a numeric factor.


Version 1.5
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New functions:
* `to_long()` to gather (transform from wide to long format) multiple column groups at once.
* S3-method `model.matrix()` for `nlme::gls` class.

Changes to functions:
* `std_beta()` now supports `nlme::gls` models.

Bug fixes:
* `word_wrap()` now removes `NA` values from `labels` before wrapping strings.
* `set_na()` now drops unused factor levels that have been replaced with `NA` values.
