This project contains primary project data, scripts used to perform Monte Carlo analyses, results of Monte Carlo analyses, and an R markdown file that generates the results and figures reported in the paper. We also provide data from a pilot study of correct productions along with R analysis files for this pilot analysis. ### Primary Analysis #### #### Primary Data #### Each data file has 3 fields: - **package**: Label for unique combination of talker, sound, and phonetic context. - **productionVoicing**: Whether the sound was classified as voiced or voiceless (n.b. for errors, this classification does not match the intended voicing). - **VOT**: Voice Onset Time for the production There are 4 data files: - [error_spontaneous.txt][1]: Spontaneously produced errors. - [correct_spontaneous.txt][2]: Spontaneously produced correct productions. - [error_experimental.txt][3]: Errors produced in tongue twister experiments. - [correct_experimental.txt][4]: Correct productions from tongue twister experiments. #### Monte Carlo Analysis Scripts #### These R scripts were used to perform Monte Carlo analyses of traces (differences between error and correct productions). There are 2 scripts: - [montecarlo_spontaneous.R][5]: Script for spontaneously produced errors. - [montecarlo_experimental.R][6]: Script for experimentally-induced errors #### Results of Monte Carlo Analyses #### The R scripts above generate date files with two fields: Correct_Means and Error_Means. These are mean VOTs (across packages) for the randomly sampled correct and error productions. - [spontaneous_10000_voiced.txt][7]: 10,000 random resamplings of spontaneously produced voiced productions. - [spontaneous_10000_voiceless.txt][8]: 10,000 random resamplings of spontaneously produced voiced productions. - [experimental_36_10000_voiced.txt][9]: 10,000 random resamplings of voiced productions in tongue twister experiments, drawn from 36 packages (the number of packages found in the spontaneous sample). - [experimental_27_10000_voiceless.txt][10]: 10,000 random resamplings of voiceless productions in tongue twister experiments, drawn from 27 packages (the number of packages found in the spontaneous sample). #### Results and Figures #### [results_and_figures.Rmd][11] is an R Markdown file that reads in the data above, calculates traces and trace ratio for the Monte Carlo resamplings, provides estimated means and *p*-values based on the Monte Carlo analysis, and builds figures to visualize the results. ### Pilot Probe of the Control Factors #### #### Pilot Data #### The data file has 11 fields: - **recordID**: Record label for each unique observation and sound file. - **sound**: Sound category, either 'b' or 'p'. - **word**: Word that the word initial stop was taken from. - **context**: Linguistic context the word was sampled from. - **stress**: Stress level, either 'stress' or 'no stress'. - **talker**: Label for the talker, either 'fc' or 'pg'. - **syllables**: Number of syllables in the sampled word. - **syllableType**: Number of syllables, either 'monosyllabic' or 'polysyllabic'. - **segmentBefore**: Last segment of the preceding word. - **segmentBeforeType**: Type of last segment of the preceding word, either 'obstruent' or 'sonorant'. - **VOT**: VOT in ms of the sampled stop (or after closure time). Data file: [correct_pilotprobe.txt][12] #### Linear Mixed Effects Analysis Script #### [lmer_pilotprobe.R][13] performs a linear mixed effects analysis on the pilot probe VOT data #### Pilot Results #### [lmer_results_pilotprobe.Rmd][14] is an R Markdown file that runs the R script file above and presents a detailed account of the model factors, results of the significance tests, and descriptive statistics on the interactions in [lmer_results_pilotprobe.pdf][15]. [1]: https://osf.io/twmr6/ [2]: https://osf.io/p82cg [3]: https://osf.io/p5yjh/ [4]: https://osf.io/v4fu7/ [5]: https://osf.io/q3h5e/ [6]: https://osf.io/3bv5n/ [7]: https://osf.io/vsaqr/ [8]: https://osf.io/brgju/ [9]: https://osf.io/rq5xy/ [10]: https://osf.io/cr7vm/ [11]: https://osf.io/qnvft/ [12]: https://osf.io/tkybr/ [13]: https://osf.io/h2jfw/ [14]: https://osf.io/z2sef/ [15]: https://osf.io/acz7v/