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.