We derived estimates 메이저놀이터of the variance explained by each regression using a recently developed variance-based R2 calculation method . These R2v values were calculated using the rsq package of R .
We report an adjusted R2v value for the number of predictors in each model (e.g., adj.R2v). In addition, whether there are multiple collinearities between predictor variables was examined using Variance Inflation Factors (VIF). The VIF evaluated a model that included individual activity frequencies and nonclassified demographic variables (e.g., age) ranging from 1.35 to 3.96 (M = 2.66), below the usual cutoff of 5 or 10.
The highest VIF variables were the attendance frequency of poker (3.96) at the Venue, e-sports (3.87) at the Venue, e-sports (3.48) online, poker (3.46) at the online, casino card/table games (3.46) at the venue and casino card/table games (3.28) at the online. The other VIFs were all < 3.00. We also examined the VIF of the model, including the range of 메이저놀이터involvement online and in the Venue. The VIF of the Online (13.58) and Venue (17.34) involvement was excluded from the regression model because it exceeded the recommended cutoff. In addition to the main regression analysis, a series of exploratory quasi-Poisson regressions were performed for each activity pair (e.g., online EGM and Venue EGM). These analyses include the frequency of gambling in each activity pair, demographic variables, the breadth of online gambling, and the breadth of involvement in venue-based gambling.
The results of these analyzes are summarized in the main text, and the complete table is provided in the supplementary information. The related VIF scores of these analyzes are shown in Additional File 1: Table S1 and the results of each regression are shown in Additional File 1: Table S2-S15. The demographic characteristics of the samples are shown in Table 1. Most participants were men, Europeans, married or de facto companionship, with the highest educational level after secondary education, working full or part-time, were born in Australia and were confirmed to not speak any language other than English at home. The participants ranged in age from 18 to 85. The PGSI score was strongly distorted (M = 3.91, SD = 5.56, Mdn = 1.00, Skew = 1.73, Kurtosis = 2.62, Min = 0, Max = 27) and similar to the Kessler 6 score (M = 5.64, SD = 6.14, Max = 3.00, Skew = 1.08, Kurtosis = 0.33, Min = 0, Max = 27).
Gambling frequency shows the frequency of participation in each online and Venue gambling activity. At each frequency level, 76.75% of the participants had experience in online gambling using lottery activities, 50.10% in sports betting, 49.80% in racing betting, and 43.95% in gambling using EGM. In venue-type gambling, 53.91% of “lottery,” 35.57% of “sports betting,” 36.57% of “race betting,” and 49.50% of “EGM” were experienced. For other online and Venue activities, there was a bias in the response that they had not participated in the past four weeks (e.g.,> = 76.15% had not participated).
The association between the frequency of participation in each gamble was examined using a series of Spearman’s Rho correlations. As shown in Table 3, a significant correlation was observed between most activities that participated online or in the Venue. A significant positive correlation was observed.