Yes, you can compare the type of litter found between sites, where stations represent the different categories and polymer types represent another categorical variable. One common approach for comparing categorical variables is using a Chi-squared test of independence.

Here's a step-by-step guide on how to perform a Chi-squared test of independence in R:

1. **Create a Contingency Table:**

First, you need to create a contingency table that represents the frequencies of each combination of station and polymer type. Assume you have the data in a data frame called `litter_data`:

```r

# Assuming 'Station' and 'Polymer_Type' are the column names in your dataset

contingency_table

we can use short - cut formules by using kimball's formula for partitioning the over all chi-squre value in the case of 2*c table

I don't think a chi-square test association works because the litter categories are not mutually exclusive.

It sounds like you have data in a form where you could use Cohran's Q test.

[ You could also use binomial logistic regression with a random effect (mixed effects generalized linear regression). ]

That is, your dependent variable is yes/no, the independent variable is polymer type, and the blocking variable is site.

I have an example here in R, with the caveat that I wrote it: https://rcompanion.org/handbook/H_07.html

Davood Omidian , Fatimah Abd