Like in Try 1, in the Test dos Hormone Years had a very high linear association having Gender, thus Hormonal Period was taken out of the newest design, just like the Gender was correlated which have Data recovery SSQ TS but Hormone Stage was not (come across Desk 9). Other predictor details targeted to possess addition had been methodically extra and you can taken out of the brand new design in accordance with the F-figure and you can multicollinearity through to the model you’ll no more be somewhat improved.
The resulting model, which had an R2 = 0.322, Adjusted R2 = 0.301, RMSE = , F(4, 130) = , p = 0.001, was as follows:
e., how long one been able to stay in VR) is negatively coordinated to help you cybersickness. Such as Check out step one, IPD non-complement was discovered to be the absolute most influential changeable, with actions diseases records. Which model taken into account thirty two.2% of variability in cybersickness. Follow-up analyses indicated that the fresh model passed the assumptions away from multiple regression along with normality and you may versatility off residuals.
Try dos Realization
Just like Check out step 1, Test 2 found that an important driver off cybersickness was IPD non-fit, accompanied by motion ailment background. Try out dos plus discover high Egg (bradygastria) and higher dropout costs (i.age., down visibility period) from the highest amounts of cybersickness. Continue reading „Table ten reveals the results about numerous linear regression research”