Editorial
Copyright ©The Author(s) 2017.
World J Methodol. Dec 26, 2017; 7(4): 112-116
Published online Dec 26, 2017. doi: 10.5662/wjm.v7.i4.112
Table 1 Statistically significant research findings can represent a true positive or false positive
Reality
Study findingsAlternative hypothesis trueNull hypothesis true
Significant P-value ≤ 0.05True positiveFalse positive
Insignificant P-value > 0.05False negativeTrue negative
Table 2 When the P-value is utilized to determine whether or not a finding is statistically significant, 1-beta represents the sensitivity for identifying the alternative hypothesis, and 1-alpha represents the specificity
Reality
Study findingsAlternative hypothesis trueNull hypothesis true
Significant P-value ≤ 0.051 - beta (power)Alpha (exact P-value)
Insignificant P-value > 0.05Beta1 - alpha
Table 3 A Type I error corresponds to 1-specificity and a Type II error corresponds to 1-sensitivity when study findings are determined to be significant or insignificant based upon the P-value
Reality
Study findingsAlternative hypothesis trueNull hypothesis true
Significant P-value ≤ 0.05CorrectType I error
Insignificant P-value > 0.05Type II errorCorrect
Table 4 This 2 × 2 contingency table shows the corresponding values for a research study where a study finding is determined to be significant based upon a P-value of 0.05 and when the study’s power is 80%
Reality
Study findingsAlternative hypothesis trueNull hypothesis true
Significant P-value ≤ 0.050.80.05
Insignificant P-value > 0.050.20.95
Table 5 P-values corrected for study power
Study powerP-value
0.950.05
0.90.047
0.850.045
0.80.042
0.750.039
0.70.037
0.650.034
0.60.032