README.Rmd

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output: github_document
---

<!-- README.md is generated from README.Rmd. Please edit that file -->

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# ciwidth

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With `ciwidth` you can determine the sample size needed for obtaining confidence intervals for means and mean differences which has a given width with a given probability. 

## Installation

You can install the development version of ciwidth from [GitHub](https://github.com/) with:

``` r
# install.packages("devtools")
devtools::install_github("snhansen/ciwidth")
```

## Example

Let us calculate the sample sizes needed to obtain a 95% confidence interval for a mean of width 5, 6, 7, 8 and 10 with a probability of either 80% or 90% and a standard deviation of 10 or 15:

```{r example}
library(ciwidth)
ci_width_mean(sigma = c(10, 15), width = 5:10, prob = c(0.80, 0.90))
```
With the `plot`-argument, you can create a `ggplot2` figure:

```{r example-figure}
ci_width_mean(sigma = c(10, 15), width = 5:10, prob = c(0.80, 0.90), plot = TRUE)
```

Since this is just a `ggplot2` figure, we can customize it afterwards:

```{r example-figure-2}
library(ggplot2)
fig <- ci_width_mean(sigma = c(10, 15), width = 5:10, prob = c(0.80, 0.90), plot = TRUE)
fig <- fig + 
  labs(x = "CI width", y = "Sample size", color = "Probability") + 
  facet_wrap(~ sigma, labeller = labeller(sigma = c("10" = "Sigma: 10", "15" = "Sigma: 15")))

fig
```