diff --git a/_freeze/mod_stats/execute-results/html.json b/_freeze/mod_stats/execute-results/html.json index d3b05ff..5986060 100644 --- a/_freeze/mod_stats/execute-results/html.json +++ b/_freeze/mod_stats/execute-results/html.json @@ -1,11 +1,9 @@ { - "hash": "88816cb66e1e3e07e77cb829ee927184", + "hash": "53d5e9af15157759f9916e3fd10baa88", "result": { "engine": "knitr", - "markdown": "---\ntitle: \"Analysis & Modeling\"\ncode-annotations: hover\n---\n\n\n## Overview\n\nGiven the wide range in statistical training in graduate curricula (and corresponding breadth of experience among early career researchers), we'll be approaching this module in a different way than the others. One half of the module will use a \"flipped approach\" where project teams will share their proposed analyses with one another. The other half of the module will be dedicated to analyses that are more common in--or exclusive to--synthesis research.\n\n## Learning Objectives\n\nAfter completing this module you will be able to: \n\n- Describe proposed analytical methods to an interested audience of mixed prior experience\n- Explain nuance in interpretation of results of proposed analyses\n- Compare and contrast interpretation of results in synthesis work versus primary research\n- Identify statistical tests common in synthesis research\n- Perform some synthesis-specific analyses\n\n## Needed Packages\n\nIf you'd like to follow along with the code chunks included throughout this module, you'll need to install the following packages:\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Note that these lines only need to be run once per computer\n## So you can skip this step if you've installed these before\ninstall.packages(\"tidyverse\")\n```\n:::\n\n\n## Mixed-Effects Models\n\n\n\n## Multi-Model Inference\n\n\n\n## Meta-Analysis\n\n\n\n## Additional Resources\n\n### Papers & Documents\n\n- [Understanding ‘It Depends’ in Ecology: A Guide to Hypothesising, Visualising and Interpreting Statistical Interactions](https://onlinelibrary.wiley.com/doi/10.1111/brv.12939). Spake _et al._, 2023. **Biological Reviews** \n- [Improving Quantitative Synthesis to Achieve Generality in Ecology](https://www.nature.com/articles/s41559-022-01891-z). Spake _et al._, 2022.**Nature Ecology and Evolution**\n- [Doing Meta-Analysis with R: A Hands-On Guide](https://bookdown.org/MathiasHarrer/Doing_Meta_Analysis_in_R/)\n\n### Workshops & Courses\n\n- Matt Vuorre's [Bayesian Meta-Analysis with R, Stan, and brms](https://mvuorre.github.io/posts/2016-09-29-bayesian-meta-analysis/)\n\n### Websites\n\n- \n", - "supporting": [ - "mod_stats_files" - ], + "markdown": "---\ntitle: \"Analysis & Modeling\"\ncode-annotations: hover\n---\n\n\n## Overview\n\nGiven the wide range in statistical training in graduate curricula (and corresponding breadth of experience among early career researchers), we'll be approaching this module in a different way than the others. One half of the module will use a \"flipped approach\" where project teams will share their proposed analyses with one another. The other half of the module will be dedicated to analyses that are more common in--or exclusive to--synthesis research. Content produced by project teams during the flipped half may be linked in the [Additional Resources](https://lter.github.io/ssecr/mod_stats.html#additional-resources) section at the bottom of this module at the discretion of each team. Otherwise the content of this module will focus only on the non-flipped content.\n\n## Learning Objectives\n\nAfter completing this module you will be able to: \n\n- Describe proposed analytical methods to an interested audience of mixed prior experience\n- Explain nuance in interpretation of results of proposed analyses\n- Compare and contrast interpretation of results in synthesis work versus primary research\n- Identify statistical tests common in synthesis research\n- Perform some synthesis-specific analyses\n\n## Needed Packages\n\nIf you'd like to follow along with the code chunks included throughout this module, you'll need to install the following packages:\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# Note that these lines only need to be run once per computer\n## So you can skip this step if you've installed these before\ninstall.packages(\"tidyverse\")\n```\n:::\n\n\n## Mixed-Effects Models\n\n\n\n## Multi-Model Inference\n\n\n\n## Meta-Analysis\n\n\n\n## Additional Resources\n\n### Papers & Documents\n\n- [Understanding ‘It Depends’ in Ecology: A Guide to Hypothesising, Visualising and Interpreting Statistical Interactions](https://onlinelibrary.wiley.com/doi/10.1111/brv.12939). Spake _et al._, 2023. **Biological Reviews** \n- [Improving Quantitative Synthesis to Achieve Generality in Ecology](https://www.nature.com/articles/s41559-022-01891-z). Spake _et al._, 2022.**Nature Ecology and Evolution**\n- [Doing Meta-Analysis with R: A Hands-On Guide](https://bookdown.org/MathiasHarrer/Doing_Meta_Analysis_in_R/)\n\n### Workshops & Courses\n\n- Matt Vuorre's [Bayesian Meta-Analysis with R, Stan, and brms](https://mvuorre.github.io/posts/2016-09-29-bayesian-meta-analysis/)\n\n### Websites\n\n- \n", + "supporting": [], "filters": [ "rmarkdown/pagebreak.lua" ], diff --git a/mod_stats.qmd b/mod_stats.qmd index 4eb4a36..083d6b9 100644 --- a/mod_stats.qmd +++ b/mod_stats.qmd @@ -5,7 +5,7 @@ code-annotations: hover ## Overview -Given the wide range in statistical training in graduate curricula (and corresponding breadth of experience among early career researchers), we'll be approaching this module in a different way than the others. One half of the module will use a "flipped approach" where project teams will share their proposed analyses with one another. The other half of the module will be dedicated to analyses that are more common in--or exclusive to--synthesis research. +Given the wide range in statistical training in graduate curricula (and corresponding breadth of experience among early career researchers), we'll be approaching this module in a different way than the others. One half of the module will use a "flipped approach" where project teams will share their proposed analyses with one another. The other half of the module will be dedicated to analyses that are more common in--or exclusive to--synthesis research. Content produced by project teams during the flipped half may be linked in the [Additional Resources](https://lter.github.io/ssecr/mod_stats.html#additional-resources) section at the bottom of this module at the discretion of each team. Otherwise the content of this module will focus only on the non-flipped content. ## Learning Objectives