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. Author manuscript; available in PMC: 2019 Mar 1.
Published in final edited form as: Am J Addict. 2018 Jan 22;27(2):116–123. doi: 10.1111/ajad.12686

Table 2.

Weighted correlation coefficients of alcohol use indicators and alcohol consequences measures.

College Student Samples
Use Indicator rw (95% CI) k N Q p I2
 Past 30-Day Frequency of Alcohol Use .397 (.364, .428) 24 11083 80.90 <.001 71.57
 Past 30-Day Frequency of Getting Drunk .474 (.448, .499) 19 6627 30.74 .031 41.45
 Typical Frequency .393 (.345, .439) 17 10223 119.83 <.001 86.65
 Typical Quantity .444 (.422, .465) 31 11852 61.43 .001 51.17
 Heaviest Quantity .421 (.389, .452) 22 8074 59.52 <.001 64.72
 Peak Quantity .412 (.384, .439) 26 11880 73.12 <.001 65.81
 Binge Drinking Frequency .466 (.442, .488) 25 8665 43.50 .009 44.83
Clinical Samples
Use Indicator rw (95% CI) k N Q p I2
 Percent Days Drinking (PDD) .158 (.045, .266) 9 4527 91.39 <.001 91.25
 Percent Heavy Drinking Days (PHDD) .266 (.188, .347) 8 4411 41.77 <.001 83.24
 Average Drinks per Drinking Day (DDD) .368 (.342, .393) 9 4527 5.75 .675 .00

Note. rw = weighted correlation coefficient based on random-effect model, k = number of studies used to compute effect sizes, Q = Cochrane’s Q statistic, which is distributed as a chi-square, and determines whether there is significant heterogeneity in the effect sizes across studies. p = p-value for the Q statistic, I2 = determines the percent of variability in effect sizes due to heterogeneity.