PomaOddsRatio {POMA} | R Documentation

## Logistic Regression Model Odds Ratios

### Description

PomaOddsRatio() calculates the Odds Ratios for each feature from a logistic regression model using the binary outcome (group/type must be a binary factor) as a dependent variable.

### Usage

    PomaOddsRatio(data, feature_name = NULL, covariates = FALSE, showCI = TRUE)

### Arguments

`data` | A MSnSet object. First `pData` column must be the subject group/type.
`feature_name` | A vector with the name/s of feature/s that will be used to fit the model. If it's NULL (default), all variables will be included in the model.
`covariates` | Logical that indicates if covariates will be included in logistic regression model. Default is `FALSE`.
`showCI` | Logical that indicates if the 95% confidence intervals will be plotted. Default is `TRUE`.

### Value

A data frame with the Odds Ratios for all features with their 95% confidence intervals and a ggplot2 object.

### Author(s)

Pol Castellano-Escuder

### Examples

    data("st000336")

    st000336 %>%
      PomaImpute() %>%
      PomaNorm() %>%
      PomaOddsRatio(feature_name = c("glutamic_acid", "glutamine",
                                     "glycine", "histidine"))

[Package POMA version 1.0.0 Index]