Man pages for dustinfife/fifer2
A Biostatisticians Toolbox for Various Activities, Including Plotting, Data Cleanup, and Data Analysis
| anchored.gradient | Create a color gradient with a color for zero |
| anchor.predictions | Generate Predictions for a Model |
| bf.bic | Compute Bayes Factor from BICs |
| bin.variables | Bin them vars |
| boxcoxR | Transform data using a boxcox transformation |
| chisq.plot | Plot Expected and Observed Frequencies (Chi Square) |
| ci.mean | Compute the confidence interval of a mean |
| clear | Clear memory of all objects |
| colored.table | Create a color-coded table in latex |
| computeTheta | Calculate inverse tangent. |
| contents | View the contents (functions) of a package |
| cor2cov | Correlation Matrix to Covariance Matrix Conversion |
| drop.columns | Drop (or keep) all columns containing a vector of strings |
| ellipse | Plots an Ellipse |
| excelCols | Generate Excel column labels |
| excelMatch | Obtain column number or variable name from Excel named... |
| generate.data | Simulate multivariate normal data |
| get.cols | Extract column index |
| gradient.legend | Create a gradiented legend |
| hash | Create useless hashes |
| icc | Compute the ICC from a lmer (package lme4) model |
| improve.fit | Compare the improvement in fit from a baseline model |
| impute.me | Multiple Imputation on a Model |
| impute.model.comparison | Compute Bayes Factor for a Imputed Model |
| intersperse | Intersperse elements of Two+ Vectors |
| jit.func | How to display data |
| last.sample | Return only one row per ID |
| make.data | Basic function for simulating bivariate data |
| make.formula | Convert strings to a formula |
| make.null | Drop or keep variables in a dataset |
| make.symmetric | Force a matrix to be symmetric |
| missing.vals | Summary of Missing Data |
| model.comparison | Perform a model comparison |
| number.to.colors | Convert from numbers to colors |
| par1 | Change default par parameters |
| par2 | Change default par parameters |
| plot.ttest | Plot ttest Summary |
| predicted.line | Create and plot a fitted line for a generalized linear model |
| print.ttest | Print ttest Summary |
| printx | Change Defaults of print.xtable |
| pval.xtable | Convert p-values into strings with inequalities. |
| r | Extract variable column indices |
| random.correlation | Generate a random correlation matrix |
| raw.alph.func | Find transparency of data |
| related.plot | Function to create a related t test plot |
| replace | Replace values in a vector |
| report.ttest | Output APA style statistical significance from a ttest object |
| rescale | Transform a variable to have a particular mean and standard... |
| residualize.lowess | Residualize a lowess function |
| rotateGraph | Rotate a graph using polar coordinates |
| scaleB | Standardize coefficients |
| sensitivity.table | Compute sensitivity/specificity/etc. |
| spread_type | Type of spread to use |
| standardized.beta | Compute standardized betas on a linear model object |
| string.to.colors | Convert between strings to colors |
| subset.sample | Sample the data |
| subsetString | Extract only part of a string |
| ttest | Perform a two-independent sample t-test |
| unfactor | Convert a factor to a character (or number) |
| x.summary | Type of x summary to use (line or mean) |
| z.test | Perform a z test |
