Here is a presentation I made for my systematic review. In the description I tried to provide additional info for each slide

I have also included a link to my data from the systematic review that I published on figshare

Here is a presentation I made for my systematic review. In the description I tried to provide additional info for each slide

I have also included a link to my data from the systematic review that I published on figshare

**1) what is the difference between a GLM and a GLMM?
**

GLM: only has fixed effects

GLMM: has fixed and random effects

both have: a set distribution and associated link function, response variable not assumed to be linear or normal, response variable should be continuous, explanatory variables are categorical and can have continuous covariates

**2)What is the difference between fixed and random effects? **

Fixed: this is the treatment in your experiment, should have an effect on your response (slope changes)

Ex: soil characteristics are the fixed effect when testing the influence of soil on plant growth of different species

Random: intercept changes but should not have an effect on your response (slope does not change)

Ex: species is a random effect when testing the influence of soil characteristics on plant growth of different species

**3) Checklist of steps for running a GLM/GLMM (Box 4 Bolker)**

- specify model: define – fixed effects, random effects, covariates, response variable,
*a priori*decide on the number of factors to include in the model - choose distribution and appropriate link function
- check assumptions: homogeniety of variances, outliers, does your distribution match the assumed distribution? (goodness of fit statistics). If variances are not homogeneous or the distribution does not match then change your model, adding effects or covariates, interactions etc
- recheck assumptions of final model (see previous step)
- check overdistribution (especially for poisson distributions)
- can choose/compare models using AIC values (lower AIC = better)

**4) Common errors that are made when performing a GLM/GLMM**

Selecting the wrong distribution and/or the wrong link function

not checking the fit of the model to the distribution

Hey everyone,

I just thought of another way we can look at our field and that is whether or not the authors determined if their data meets the assumptions of the stats test they are running.

Just a thought!

My research project will be looking at restoration ecology and the stats tests used within this field. More specifically, I will be looking at studies investigating methods of restoring invaded ecosystems.

Hey everyone!

Here is the list of possible analyses to do for our systematic review that we discussed in class yesterday

1) How statistical tests changed by year

2) Impact factor of journals

3) How stats influence citation rate of appers

4) Diversity of tests used in your field

5) The classification (central tendency, randomized, algorithm) of tests your field uses

6) How often stats are used in your field

7) Sample sizes used in your field

8) Stats tests used by country

9) What factors are used in your field – subdominant search terms

edited version