statsmodels.stats.proportion._score_confint_inversion

statsmodels.stats.proportion._score_confint_inversion(count1, nobs1, count2, nobs2, compare='diff', alpha=0.05, correction=True)[source]

Compute score confidence interval by inverting score test

Parameters:

  • count1 – Count and sample size for first sample.

  • nobs1 – Count and sample size for first sample.

  • count2 – Count and sample size for the second sample.

  • nobs2 – Count and sample size for the second sample.

  • compare (string in ['diff', 'ratio' 'odds-ratio']) – If compare is diff, then the confidence interval is for diff = p1 - p2. If compare is ratio, then the confidence interval is for the risk ratio defined by ratio = p1 / p2. If compare is odds-ratio, then the confidence interval is for the odds-ratio defined by or = p1 / (1 - p1) / (p2 / (1 - p2).

  • alpha (float in interval (0,1)) – Significance level, e.g. 0.05, is the probability of a type I error, that is wrong rejections if the Null Hypothesis is true.

  • correction (bool) – If correction is True (default), then the Miettinen and Nurminen small sample correction to the variance nobs / (nobs - 1) is used. Applies only if method=’score’.

Returns:

  • low (float) – Lower confidence bound.

  • upp (float) – Upper confidence bound.