Predictor importance for predicting stock market using neural network and linear predictor. by Dania AL-Najjar (11840857)

Multivariable linear regression analyses for predicting factors. by Maurice Pradella (11678817)

Multivariable general linear mixed models for retinal thickness measurements. by Roomasa Channa (374127)

Multivariable general linear mixed model for GC-IPL thickness among participants with diabetes. by Roomasa Channa (374127)

Summary of point estimates burnout at the follow-up survey from the multivariable generalized linear regression assessing the impact of wellbeing, workplace, and demographic variab... by Sarah Elizabeth Scales (12972097)

Predictors’ importance on the pH. by Bulent Gucyetmez (849602)

Association between CAP value and carotid-femoral pulse wave velocity. by Johannes Nairz (18010746)

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Characteristics of the study population. by Johannes Nairz (18010746)

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Boxplot mean cfPWV comparisons. by Johannes Nairz (18010746)

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Study flow chart. by Johannes Nairz (18010746)

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Predictors in ordinal regression model for GDS. by Shane Naidoo (20148021)

“…Conversely in a linear regression model, depression (<i>B</i> = -2.01, <i>p</i> = .004) and physical activity (<i>B</i> = -.001, <i>p</i> = .008) were predictors for decreases in BMI.…”

Actions of the main intrinsic laryngeal muscles and the laryngeal abnormalities in Parkinson’s disease. by Andrew Ma (4532494)

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The laryngeal measures. by Andrew Ma (4532494)

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Change in laryngeal measures with disease duration and UPDRS part III scores. by Andrew Ma (4532494)

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Comparison of the laryngeal measures during vocalization between pwPD and controls. by Andrew Ma (4532494)

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Demographic details. by Andrew Ma (4532494)

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Predictors used in the modelling analysis. The ‘Snail count’ model refers to the Generalised Linear Mixed Model (GLMM) used to model snail counts, ‘Prevalence’ refers to the diseas... by Roland Proud (11764892)

Fig 2 - by Dania AL-Najjar (11840857)

Fig 3 - by Dania AL-Najjar (11840857)

Database used for analysis. by Colins O. Oduma (9964722)

“…Three to 34 larval habitats per cluster and 0–17 habitats within a 250m radius around households were observed. Using a generalized linear mixed effect model (GLMM), a 5% decrease in the odds of getting infected per each 10m increase in altitude was observed, while the number of larval habitats and their proximity to households were not statistically significant predictors for prevalence. …”