Predictor variables and multivariate analysis using vaspin as a dependent variable Step Parameter
Predictor variable: [r.sup.2] =0.077 Birth length Multivariate analysis ([r.sup.2] =0.132, p=0.018)
Predictor variables: birth weight, birth length, cephalic perimeter 1 Birth weight 2 Birth length 3 Cephalic perimeter
Predictor variable: [r.sup.2] =0.132 Glucose Multivariate analysis ([r.sup.2] =0.140, p=0.003)
Predictor variables: glucose, insulin 1 Glucose 2 Insulin Step [beta] [+ or -] s.e.m.
These zones are reflecting northing which proves the dominating behaviour of the
predictor variable during high precipitation.
The tool identifies and quantifies what impact each
predictor variable has on the model's output.
Age of sexual maturity was found the most
predictor variable that affecting EP and it was followed by hatching period.
Bivariate logistic regression was performed to determine the association between the
predictor variable of TPB and education, age, gender, FGM status of females in the household and location of residence of parents on intention.
Table 1 presents the RC of the
predictor variable in the different epidemic waves.
Equation 1 shows a simplified version of the model where [X.sub.i] are the
predictor variable and [[beta].sub.i] are the coefficients.
Therefore we did not include the
predictor variable PARA (brood parasitism) in our analyses for Northern Cardinals.
Predictor Variable The coefficient t-statistics of determination ([R.sup.2]) Perceived quality 0.609 4.994
Predictor Variable Correlation Path Coefficient coefficient ([beta]) Perceived quality 0.640 0.394 Based on the t statistics of perceived quality is at the 99 percent of confidence level and has significant impact on relation quality, so the first hypothesis is confirmed.
Apart from single skin-fold thicknesses, also the sum of skin-folds has been reported as an important
predictor variable [41-43].
95% CI Regressions with A2
predictor variable = Any disorder Any A2 0.09 *** [0.07,0.11] disorder Regressions with A2
predictor variable = Number of disorders 1 A2 disorder 0.06 *** [0.03,0.08] 2 + A2 0.13 *** [0.11,0.16] disorders Regressions with A2
predictor variable = Type of disorder Paranoid 0.06 ** [0.02,0.10] Schizoid 0.01 [-0.03,0.06] Schizotypal 0.01 [-0.03,0.05] Antisocial 0.11 *** [0.05,0.171 Borderline 014 *** [0.10,0.18] Histrionic -0.01 [-0.06,0.04] Narcissistic 0.02 [-0.01,0.05] Avoidant -0.00 [-0.05,0.04] Dependent -0.01 [-0.09,0.08] Obsessive- 0.02 [-0.01,0.06] compulsive Specification b ([double dagger]) Risk Diff.
Equation 1 shows a simplified version of the model where Xi are the
predictor variable and [[beta].sub.i] are the coefficients.