## Thoughts on implementing TRACE in R

Code doesn’t lie.

Code doesn’t lie.

Useful Github page alert: Dean Attali has started collecting links to RStudio addins, including the one I made for wrapping text in RMarkdown.

Code doesn’t lie.

No, not the cha-ching kind of machine

Randomly sampling subsets of data

Weighted wiggles and smoothed categories

What looks plausible, what fits, what does both

Creating a diagram to illustrate information borrowing (partial pooling)

This time in LaTeX

There are a lot of bilabial sounds in that title

Modeling left-handedness in Stan

Summarizing many, many lines of fit

Trial by 🔥

It’s getting faster. Moving faster now. It’s getting out of hand

The ggplot2 version of multiplying by 1

Weighted wiggles and smoothed categories

What looks plausible, what fits, what does both

Creating a diagram to illustrate information borrowing (partial pooling)

Posterior predictive values and the like.

Randomly sampling subsets of data

Making a graph, connecting nodes twice

Because the functions expect a list of expressions.

Bottling up magic spells

Plus some growth curve analysis!

Less Q Q, more pew pew

What looks plausible, what fits, what does both

Creating a diagram to illustrate information borrowing (partial pooling)

It culiminates in a highlighted math equation.

\/\/\////\/\/\/\////\/\//\/\/\\//\\\/\

It’s getting faster. Moving faster now. It’s getting out of hand

The ggplot2 version of multiplying by 1

Making a graph, connecting nodes twice

Creating an RSS feed for R blog posts.

Now you can have Fairy Floss in quarterly-report.docx

A lesson from debugging source()

Tidying and splitting model summaries for inline reporting

Some basic uses of nonstandard evaluation.

Useful Github page alert: Dean Attali has started collecting links to RStudio addins, including the one I made for wrapping text in RMarkdown.

Weighted wiggles and smoothed categories

Less Q Q, more pew pew

It culiminates in a highlighted math equation.

Creating an RSS feed for R blog posts.

Weighted wiggles and smoothed categories

Weighted wiggles and smoothed categories

Tidying and splitting model summaries for inline reporting

What looks plausible, what fits, what does both

Creating a diagram to illustrate information borrowing (partial pooling)

There are a lot of bilabial sounds in that title

Plus some growth curve analysis!

Code doesn’t lie.

It culiminates in a highlighted math equation.

A lesson from debugging source()

Randomly sampling subsets of data

No, not the cha-ching kind of machine

Bottling up magic spells

Because the functions expect a list of expressions.

Now you can have Fairy Floss in quarterly-report.docx

That pesky ampersand.

Tidying and splitting model summaries for inline reporting

Tidying and splitting model summaries for inline reporting

Now you can have Fairy Floss in quarterly-report.docx

Find a match() in your base R library

A lesson from debugging source()

A simulation study of the mighty Slay the Spire relic

`&&`

as a stricter `&`

A crash course on the ands and ors in R

Weighted wiggles and smoothed categories

Tidying and splitting model summaries for inline reporting

Less Q Q, more pew pew

What looks plausible, what fits, what does both

Creating a diagram to illustrate information borrowing (partial pooling)

beep boop the intraclass correlation indicates STRONG interrater reliability

It culiminates in a highlighted math equation.

Randomly sampling subsets of data

\/\/\////\/\/\/\////\/\//\/\/\\//\\\/\

It’s getting faster. Moving faster now. It’s getting out of hand

Wait, what’s wrong with seven ifelse statements?

No, not the cha-ching kind of machine

Making a graph, connecting nodes twice

The ggplot2 version of multiplying by 1

Bottling up magic spells

The tidyverse version of dataframes

There are a lot of bilabial sounds in that title

Plus some growth curve analysis!

Modeling left-handedness in Stan

The coupon collector’s problem

Doing the same thing over and over again

Summarizing many, many lines of fit

Some basic uses of nonstandard evaluation.

That pesky ampersand.

Because the functions expect a list of expressions.

Posterior predictive values and the like.

Code doesn’t lie.

No, not the cha-ching kind of machine

No, not the cha-ching kind of machine

Bottling up magic spells

Now you can have Fairy Floss in quarterly-report.docx

There are a lot of bilabial sounds in that title

Summarizing many, many lines of fit

Trial by 🔥

Some basic uses of nonstandard evaluation.

beep boop the intraclass correlation indicates STRONG interrater reliability

A simulation study of the mighty Slay the Spire relic

Now you can have Fairy Floss in quarterly-report.docx

Weighted wiggles and smoothed categories

Wait, what’s wrong with seven ifelse statements?

Because the functions expect a list of expressions.

Weighted wiggles and smoothed categories

Modeling left-handedness in Stan

That pesky ampersand.

Now you can have Fairy Floss in quarterly-report.docx

What looks plausible, what fits, what does both

Creating a diagram to illustrate information borrowing (partial pooling)

Code doesn’t lie.

Making a graph, connecting nodes twice