For many tasks in statistical hypothesis testing, it is necessary to find the ordinate value where the cumulative distibution function reaches a particular value (inverse of the CDF). These functions are available in Matlab's stats toolbox, but to allow users without this toolbox to use NeuroElf, freely available code has been edited and put into one compound function, sdist.

  sdist  - statistics distributions
 
  FORMAT:       d = sdist(type, variate, df1 [, df2 [, pin]])
 
  Input fields:
 
        type        either of 'betacdf', 'betainv', 'betapdf',
                    'fcdf', 'finv', 'fpdf', 'tcdf', 'tinv', 'tpdf'
        variate     variate (or p-value)
        df1, df2    d.f. (or other required parameter)
        pin         logical flag, inverse from 0.9 to 0.1 logic
 
  Output fields:
 
        d           determined value of requested distribution function

• find the value required to threshold a t-map with 25 degrees of freedom at p<0.005 (uncorr.):

  sdist('tinv', 0.995, 25)

• find the value required to threshold an F-map with (3, 20) degrees of freedom at p<0.01 (uncorr.):

  sdist('finv', 0.99, 3, 20)

• find out if a given t-statistic (3.314, df = 115) is enough to meet a specific alpha criterion (0.001):

  sdist('tcdf', 3.314, 115) >= 0.999