continuity correction
correction for continuity

The test was used with continuity correction, and values of p<0.05 were considered to be significant.

This addition of 1/2 to x is a continuity correction.

Two-tailed significance tests were used throughout, and continuity corrections applied where appropriate.

Continuity correction was used to determine the P values of Χ 2tests.

Comment and suggestion on the Yates continuity correction.

This is called the continuity correction.

The addition of 0.5 is the continuity correction; the uncorrected normal approximation gives considerably less accurate results.

The continuity correction.

Use of Normal as an approximation to the Binomial and Poisson, continuity correction.

A continuity correction can also be applied when other discrete distributions supported on the integers are approximated by the normal distribution.

The chi-square test calculates approximate P values, and the Yates' continuity correction is designed to make the approximation better.

The following formulae for the lower and upper bounds of the Wilson score interval with continuity correction are derived from Newcombe (1998).

However, simulations have shown both the exact binomial test and the McNemar test with continuity correction to be overly conservative.

But, upon approximating a discrete random quantity by a continuous random quantity, a continuity correction is required:

In probability theory, a continuity correction is an adjustment that is made when a discrete distribution is approximated by a continuous distribution.

Where extreme accuracy is not necessary, computer calculations for some ranges of parameters may still rely on using continuity corrections to improve accuracy while retaining simplicity.

The Wilson interval may be modified by employing a continuity correction, in order to align the minimum coverage probability (rather than the average) with the nominal value.

Just as the Wilson interval mirrors Pearson's chi-squared test, the Wilson interval with continuity correction mirrors the equivalent Yates' chi-squared test.

The chi-square statistic with Yates continuity correction was computed according to the definition: Spatial proximity of constrained word pairs The second requirement for a conserved sequence template involved constraints on spatial arrangements between individual words.

Before the ready availability of statistical software having the ability to evaluate probability distribution functions accurately, continuity corrections played an important role in the practical application of statistical tests in which the test statistic has a discrete distribution: it was a special importance for manual calculations.

In this case Yate's correction for continuity is applied.

Yates’s correction for continuity and the analysis of 2 x 2 contingency tables.

In performing the test, Yates's correction for continuity is often applied, and simply involves subtracting 0.5 from the observed values.

Some packages incorrectly treat ties or fail to document asymptotic techniques (e.g., correction for continuity).

In statistics, 'Yates' correction for continuity', or 'Yates' chi-square test' is used in certain situations when testing for independence in a contingency table.

For data with small sample size, such as no marginal total is greater than 15 (and consequently ), one should utilize Yates's correction for continuity or Fisher's exact test.

Before analysis, we categorised continuous exposure variables into approximate quartiles and then performed univariate analysis for each potential risk factor using Pearson's chi-square test without correction for continuity.

In this case, a better approximation can be obtained by reducing the absolute value of each difference between observed and expected frequencies by 0.5 before squaring; this is called Yates's correction for continuity.

To reduce the error in approximation, Frank Yates suggested a correction for continuity that adjusts the formula for Pearson's chi-square test by subtracting 0.5 from the difference between each observed value and its expected value in a 2 x 2 contingency table.