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Background: Data with ordinal categories occur in many diverse areas, but methodologies for modeling ordinal data lag severely behind equivalent methodologies for continuous data. There are advantages to using a model specifically developed for ordinal data, such as making fewer assumptions and having greater power for inference. Methods: The ordered stereotype model (OSM) is an ordinal regression model that is more flexible than the popular proportional odds ordinal model. The primary benefit of the OSM is that it uses numeric encoding of the ordinal response categories without assuming the categories are equally-spaced. Results: This article summarizes two recent advances in the OSM: (1) three novel tests to assess goodness-of-fit; (2) a new Generalized Estimating Equations approach to estimate the model for longitudinal studies. These methods use the new spacing of the ordinal categories indicated by the estimated score parameters of the OSM. Conclusions: The recent advances presented can be applied to several fields. We illustrate their use with the well-known arthritis clinical trial dataset. These advances fill a gap in methodologies available for ordinal responses and may be useful for practitioners in many applied fields This research has been supported by Marsden grant E2987-3648 administrated by the Royal Society of New Zealand, by grant 2017 SGR 622 (GRBIO) administrated by the Departament d’Economia i Coneixement de la Generalitat de Catalunya (Spain) and by the Ministerio de Ciencia e Innovación (Spain) [PID2019-104830RB-I00/ DOI (AEI): 10.13039/501100011033].

We propose a method for visualizing genetic assignment data by characterizing the distribution of genetic profiles for each candidate source population. This method enhances the assignment method of Rannala and Mountain (1997) by calculating appropriate graph positions for individuals for which some genetic data are missing. An individual with missing data is positioned in the distributions of genetic profiles for a population according to its estimated quantile based on its available data. The quantiles of the genetic profile distribution for each population are calculated by approximating the cumulative distribution function (CDF) using the saddlepoint method, and then inverting the CDF to get the quantile function. The saddlepoint method also provides a way to visualize assignment results calculated using the leave-one-out procedure. This new method offers an advance upon assignment software such as geneclass2, which provides no visualization method, and is biologically more interpretable than the bar charts provided by the software structure. We show results from simulated data and apply the methods to microsatellite genotype data from ship rats (Rattus rattus) captured on the Great Barrier Island archipelago, New Zealand. The visualization method makes it straightforward to detect features of population structure and to judge the discriminative power of the genetic data for assigning individuals to source populations.

Bridging/foundation programmes are often provided by tertiary institutions to increase equity in access and academic performance of students from under-served communities. Little empirical evidence exists to measure the effectiveness of these bridging/foundation programmes on undergraduate academic outcomes. This research identifies the predictive effect of academic outcomes achieved within a bridging/foundation programme, targeted towards indigenous and ethnic minority students, on first-year degree-level outcomes. Overall performance within the bridging/foundation programme was positively associated with increasing Grade Point Average (GPA), ‘Core 4’ GPA and passing all courses in first year. However, mixed associations were identified between feeder bridging/foundation courses and their intended first year course counterparts. These findings support the continued provision of bridging/foundation education; however, curricular reform within the bridging/foundation programme was required. Key development...

Background Tertiary institutions are struggling to ensure equitable academic outcomes for indigenous and ethnic minority students in health professional study. This demonstrates disadvantaging of ethnic minority student groups (whereby Indigenous and ethnic minority students consistently achieve academic outcomes at a lower level when compared to non-ethnic minority students) whilst privileging non-ethnic minority students and has important implications for health workforce and health equity priorities. Understanding the reasons for academic inequities is important to improve institutional performance. This study explores factors that impact on academic success for health professional students by ethnic group. Methods Kaupapa Māori methodology was used to analyse data for 2686 health professional students at the University of Auckland in 2002–2012. Data were summarised for admission variables: school decile, Rank Score, subject credits, Auckland school, type of admission, and bridging programme; and academic outcomes: first-year grade point average (GPA), first-year passed all courses, year 2 – 4 programme GPA, graduated, graduated in the minimum time, and composite completion for Māori, Pacific, and non-Māori non-Pacific (nMnP) students. Statistical tests were used to identify significant differences between the three ethnic groupings. Results Māori and Pacific students were more likely to attend low decile schools (27 % Māori, 33 % Pacific vs. 5 % nMnP, p

Tertiary institutions internationally aim to increase student diversity, however are struggling to achieve equitable academic outcomes for indigenous and ethnic minority students and detailed exploration of factors that impact on success is required. This study explored the predictive effect of admission variables on academic outcomes for health professional students by ethnic grouping. Kaupapa Māori and Pacific research methodologies were used to conduct a quantitative analysis using data for 2686 health professional students [150 Māori, 257 Pacific, 2279, non-Māori non-Pacific (nMnP)]. The predictive effect of admission variables: school decile; attending school in Auckland; type of admission; bridging programme; and first-year bachelor results on academic outcomes: year 2-4 grade point average (GPA); graduating; graduating in the minimum time; and optimal completion for the three ethnic groupings and the full cohort was explored using multiple regression analyses. After adjusting for admission variables, for every point increase in first year bachelor GPA: year 2-4 GPA increased by an average of 0.46 points for Māori (p = 0.0002, 95% CI 0.22, 0.69), 0.70 points for Pacific (p

Context Wireless sensor networks (WSNs) are revolutionising areas of animal behaviour research and are advantageous based on their ability to be deployed remotely and unobtrusively, for long time periods in inaccessible areas. Aims We aimed to determine the feasibility of using a WSN to track detailed movement paths of small animals, e.g. rats (Rattus spp.) 100–400g, too small for current GPS technology, by calibrating active Radio Frequency Identification (RFID) tags and loggers using Radio Frequency Signal Strength Indicator (RSSI) as a proxy for distance. Active RFIDs are also called Wireless Identification (WID) tags. Methods Calibration tests were conducted using a grid of loggers (n=16) spaced at 45-m intervals in clear line-of-sight conditions. WID tags (n=16) were placed between the loggers at 45-m intervals. Eight ‘walks’ were also conducted through the grid using a single WID tag. This involved attaching the tag to a small bottle of water (to simulate the body of an animal), towed around the grid using a 1-m long tow line attached to a volunteer walker. The volunteer also held a GPS device that logged their track. Models were constructed to test the effects of distance, tag movement and individual differences in loggers and tags on the reliability of movement data. Key results Loggers were most successful at detecting tags at distances

Background Universities should provide flexible and inclusive selection and admission policies to increase equity in access and outcomes for indigenous and ethnic minority students. This study investigates an equity-targeted admissions process, involving a Multiple Mini Interview and objective testing, advising Māori and Pacific students on their best starting point for academic success towards a career in medicine, nursing, health sciences and pharmacy. Methods All Māori and Pacific Admission Scheme (MAPAS) interviewees enrolled in bridging/foundation or degree-level programmes at the University of Auckland were identified (2009 to 2012). Generalised linear regression models estimated the predicted effects of admission variables (e.g. MAPAS Maths Test; National Certificate in Educational Achievement (NCEA) Rank Score; Any 2 Sciences; Followed MAPAS Advice) on first year academic outcomes (i.e. Grade Point Average (GPA) and Passes All Courses) adjusting for MAPAS interview year, gender, ancestry and school decile. Results 368 First Year Tertiary (bridging/foundation or degree-level) and 242 First Year Bachelor (degree-level only) students were investigated. NCEA Rank Score (estimate 0.26, CI: 0.18-0.34, p

Erratum to ‘‘Inertial sensor-based knee flexion/extension angle estimation’’ [J. Biomech. 42 (2009) 2678–2685] Glen Cooper , Ian Sheret , Louise McMillan , Konstantinos Siliverdis , Ning Sha , Diana Hodgins , Laurence Kenney , David Howard a a Centre for Rehabilitation and Human Performance Research, University of Salford, UK b Analyticon, Tessella Support Services Plc, Stevenage, UK c European Technology for Business Ltd., Codicote, UK