statistical power

Next, we consider the effects of both aspects on statistical power.

"It's possible that we did not have enough statistical power."

The number of events in a study determines its statistical power.

However, the latest research followed patients for almost twice as long and had greater statistical power.

This, in turn, may increase the statistical power to detect an effect.

This is described as the "Statistical power" of the trial.

The larger the sample size or number of participants in the trial, the greater the statistical power.

The statistical power of the latter trial has been questioned.

The desired statistical power of the trial, shown in column to the left.

It is also important to consider the statistical power of a hypothesis test when interpreting its results.

Research on the statistical power of the therapeutic relationship now reflects more than 1,000 findings.

The precision with which the data are measured also influences statistical power.

First, some studies may have lacked statistical power to detect interactions.

Note however that an increase of statistical power comes at a price: more tests are required, each subject having to be tested twice.

This leads to its use in statistics, especially calculating statistical power.

"But there's not enough statistical power, given all the possibilities, to be confident of when it's happening in specific players."

It has more statistical power than the Friedman test against the alternative that there is a difference in trend.

Statistical power may depend on a number of factors.

Increasing sample size is often the easiest way to boost the statistical power of a test.

It did not have enough statistical power to tell whether people who got less appropriate or needed care were more likely to die as a result.

This grants the researcher more statistical power to detect differences within the data.

Statistical power relies in part on high sample size.

The statistical power to detect differences was much reduced when 3 samples per group were analyzed instead of 4.

Isolated cases are more likely to be available than sibling pairs, increasing the potential for statistical power.

In empirical testing this modification is conservative but appears to have low statistical power.