Skip to content

HTTPS clone URL

Subversion checkout URL

You can clone with HTTPS or Subversion.

Download ZIP
Scripts for analyzing the results from the DIVA Intensity Shift Experiment (CadLab)
Matlab
branch: master

Fetching latest commit…

Cannot retrieve the latest commit at this time

Failed to load latest commit information.
.gitignore
README.md
intShift_analysis_1.m
intShift_readSubjData.m
pert_analysis.m

README.md

DIVAIntAnalysis

Scripts for analyzing the results from the DIVA Intensity Shift Experiment (CadLab)

Main program: intShift_analysis_1.m

You will need to modify lines 15 and 24 for 1) where the two data folders (DN and UP) are and 2) where the individual-subject plots will be saved

Usage: intShift_analysis_1(bCD, nStresses, reverseOpt, otherOpts) Inputs: bCD - a 0/1 variable that indicates whether contrast distance (1) or asbolute values (0) are shown. nStresse - vector for specifying the stress positions to include in the analysis. e.g., [1, 2] - both sentences with stress on word 1 and sentences with stress on word 2 [1] - only sentences with stress on word 1

reverseOpt - option to reverse stressed and unstressed, for looking at the absolute values from the unstressed words. NOTE: this option only works under bCD = 0. Do not use this option with bCD = 1. For example, if you want to look at the absolute values from the unstressed words (words 1 or 2) of all sentences Do: intShift_analysis_1(0, [1, 2], 'reverse') Or, if you want to look at the absolute values from the unstressed words on position 1, do: intShift_analysis_1(0, [2], 'reverse') Note that we put [2], instead of [1] here, because when word 2 is stressed, word 1 is unstressed.

otherOpts - additional options, such as "showByEpoch" and "showIndS" (see examples below).

Usage exapmles:

  1. Contrast distance, from stressed words as both position 1 and 2: intShift_analysis_1(1, [1, 2])
  2. Same as above, but show epoch-by-epoch data: intShift_analysis_1(1, [1, 2], 'showByEpoch')
  3. Same as above, but show data from individual subjects: intShift_analysis_1(1, [1, 2], 'showIndS')
  4. Absolute values, from stressed words at positions 1 and 2: intShift_analysis_1(0, [1, 2])
  5. Absolute values, from only stressed words at position 2: intShift_analysis_1(0, [2])
  6. Absolute values, from unstressed words at positions 1 and 2: intShift_analysis_1(0, [1, 2], 'reverse')
  7. Show composite prosody adaptation (CPA) scores, by phase: intShift_analysis_1(1, [1, 2], 'cpa')
  8. Show CPA scores, by phase and by epoch: intShift_analysis_1(1, [1, 2], 'cpa', 'showByEpoch')

  9. Show CPA scores and perfor permutation test (10000 times): intShift_analysis_1(1, [1, 2], 'cpa', 'permute', 10000)

  10. Analyze the correlation between the adaptation measures and the pertContr: intShift_analysis_1(1, [1, 2], 'cpa', 'corrPert')

    Note: you may need to revise the "L3_DATA_DIR" variable to set the correct path to the level-3 (in Kevin's parlance) csv files.

  11. Use the rank-sum and signed rank tests, instead of the default t-tests; perform random permutation for 10,000 iterations, and do not show the uncorrected p-values in the figures: intShift_analysis_1(1, [1, 2], 'cpa', 'loadCache', 'rs', 'permute', 10000, 'noUnc')

  12. Use subtraction-based normalization, instead of the default divsion-based one. intShift_analysis_1(1, [1, 2], 'subtr', 'loadCache', 'rs', 'permute', 1000)

Something went wrong with that request. Please try again.