Quantitative analysis of a Māori and Pacific admission process on first-year health study

BMC Medical Education

Table 9 Multiple regression analysis results – logistic regression^a

Multivariate analysis results	First year tertiary students		First year bachelor students
Multivariate analysis results	2009 – 2012 (n = 368)		2009 – 2012 (n = 242)
	Odds ratio (95 % CI)	P value	Odds ratio (95 % CI)	P value
Passes All Eight Courses
NCEA Rank Score (per 20 point increase)	1.10 (0.98, 1.27)	0.112	1.46 (1.24, 1.74)	<0.0001
Followed MAPAS advice
No	1.00		1.00
Yes	5.40 (2.36, 12.39)	<0.0001	3.34 (1.45, 7.69)	0.005
Any 2 sciences
No	1.00		1.00
Yes	2.30 (1.15, 4.61)	0.019	1.36 (0.55, 3.33)	0.504
MAPAS Maths test (per 10 % increase)	1.13 (0.95, 1.33)	0.179	1.08 (0.90, 1.32)	0.392
Passes All Core 4 Courses
NCEA Rank Score (per 20 point increase)	–	–	1.48 (1.24, 1.74)	<0.0001
Followed MAPAS advice	–	–
No			1.00
Yes	–	–	3.27 (1.39, 7.69)	0.0067
Any 2 sciences	–	–
No			1.00
Yes	–	–	1.95 (0.78, 4.84)	0.1513
MAPAS Maths test (per 10 % increase)	–	–	1.10 (0.91, 1.34)	0.3156

^aAdjusted for MAPAS interview year, gender, ancestry and school decile. For Passes All Courses (a binary outcome variable), the odds ratio (OR) associated with the change in a linear predictor was estimated with 95 % confidence interval. For a continuous predictor, this indicated the difference in ratio of two odds with either 20 point (NCEA Rank Score) or 10 % (MAPAS Maths test) increase in the predictor, relative to the odds with no increase. For a categorical predictor, this indicated the difference in odds between the current and reference categories (e.g. the odds of Passes All Courses with exposure to Any 2 Sciences, relative to the odds of not having exposure to Any 2 Sciences). The null hypothesis was that there was no change in the odds (i.e. OR = 1)

ISSN: 1472-6920