Dependent Berkson errors in linear and nonlinear models

Often predictor variables in regression models are measured with errors. This is known as an errors-in-variables (EIV) problem. The statistical analysis of the data ignoring the EIV is called naive analysis. As a result, the variance of the errors is underestimated. This affects any statistical inference that may subsequently be made about the model parameter estimates or the response prediction. In some cases (e.g. quadratic polynomial models) the parameter estimates and the model prediction is biased. The errors can occur in different ways. These errors are mainly classified into classical (i.e. occur in observational studies) or Berkson type (i.e. occur in designed experiments). This thesis addresses the problem of the Berkson EIV and their effect on the statistical analysis of data fitted using linear and nonlinear models. In particular, the case when the errors are dependent and have heterogeneous variance is studied. Both analytical and empirical tools have been used to develop new approaches for dealing with this type of errors. Two different scenarios are considered: mixture experiments where the model to be estimated is linear in the parameters and the EIV are correlated; and bioassay dose-response studies where the model to be estimated is nonlinear. EIV following Gaussian distribution, as well as the much less investigated non-Gaussian distribution are examined. When the errors occur in mixture experiments both analytical and empirical results showed that the naive analysis produces biased and inefficient estimators for the model parameters. The magnitude of the bias depends on the variances of the EIV for the mixture components, the model and its parameters. First and second Scheffé polynomials are used to fit the response. To adjust for the EIV, four different approaches of corrections are proposed. The statistical properties of the estimators are investigated, and compared with the naive analysis estimators. Analytical and empirical weighted regression calibration methods are found to give the most accurate and efficient results. The approaches require the error variance to be known prior to the analysis. The robustness of the adjusted approaches for misspecified variance was also examined. Different error scenarios of EIV in the settings of concentrations in bioassay dose-response studies are studied (i.e. dependent and independent errors). The scenarios are motivated by real-life examples. Comparisons between the effects of the errors are illustrated using the 4-prameter Hill model. The results show that when the errors are non-Gaussian, the nonlinear least squares approach produces biased and inefficient estimators. An extension of the well-known simulation-extrapolation (SIMEX) method is developed for the case when the EIV lead to biased model parameters estimators, and is called Berkson simulation-extrapolation (BSIMEX). BSIMEX requires the error variance to be known. The robustness of the adjusted approach for misspecified variance is examined. Moreover, it is shown that BSIMEX performs better than the regression calibration methods when the EIV are dependent, while the regression calibration methods are preferable when the EIV are independent.EThOS - Electronic Theses Online ServiceSaudi Ministry of Higher EducationGBUnited Kingdo

Assessment of Medical Students’ Attitudes Towards Research and Perceived Barriers

Background: Health research has been integrated as part of the curriculum of many health sciences teaching universities. The aim of this study is to measure the attitude of medical students towards research. Methods: A cross-sectional survey study was conducted from March to May 2016 using the Student Attitude Towards Research (SAR) scale. The survey was distributed amongst undergraduate medical students at the College of Medicine, King Saud bin Abdul-Aziz University for Health Sciences, Riyadh, Saudi Arabia. Main outcome measure was score on attitude scale with 15 Likert-type statements. Results: A total of 237 responses were collected from the students (55.6% males and 44.3% females). In general, students agreed that ‘research is important for identifying and investing problems in a subject matter’ (N=206, 86.9%). Female students showed significantly more positive attitude towards research (P<0.05). In regards to the degree of involvement of the faculty in the research program, 35% of students agreed that it was acceptable, and 48.1% agreed that the faculty members have adequate skills to handle research methodology. Conclusion: Most of the surveyed students were aware of the importance of undertaking medical research, but their attitude to the field was not always positive. There is an urgent need to introduce research programs as a part of the curriculum of all medical colleges, and ensure that these programs meet their goals and continue to be improved by providing good infrastructural facilities in order to provide skillful physicians to support research related activities

Cultural and academic barriers toward physician-scientist (MD-PhD) careers: A mixed methods study

AbstractIn Saudi Arabia, there is yet to be a single MD-PhD program established despite calls for its implementation. Herein, we assess students’ and stakeholders’ perceived barriers and opinions towards the implementation of such a program. A mixed-method design was used. For the quantitative part, a sample of 190 medical students completed a pre-validated survey that addressed procedural, bureaucratic, and environmental challenges to the implementation of the program. In addition, three semi-structured interviews with stakeholders had been carried out to address the implementation of an MD-PhD track. While the semi-structured interviews resulted in a wide array of responses, most students indicated that limited funding (55.7%) and predicted high workload (63.2%) were amongst the most significant hurdles to enrolling in an MD-PhD if offered to do so. In addition, first-generation students and female students were less likely to encourage the establishment of such a program. This study reported multiple significant barriers to pursuing an MD-PhD track in the Kingdom of Saudi Arabia. The findings of this study reflect the complexity of implementing an MD-PhD program in the country and can be useful for concerning bodies to holistically consider predicted barriers that students may face when establishing an MD-PhD