Specifically designed for the MCEM Part C, this book contains 100 questions to help candidates prepare for this OSCE examination. All questions and answers are mapped directly to the College of Emergency Medicine syllabus and contain detailed information that allows candidates to appreciate the format and requirements of each OSCE. Each question features instructions to candidate, actor, and examiner, so candidates can practise in groups and recreate OSCE stations. MCEM-style marking sheets ensure that candidates have a good understanding of the standard that is required by the College. Written by a team with many years of experience of running mock OSCE exams for trainees, this book will give candidates a realistic and comprehensive preparation for the MCEM Part C.

Specifically designed for the MCEM Part C, this book contains 100 questions to help candidates prepare for this OSCE examination. All questions and answers are mapped directly to the College of Emergency Medicine syllabus and contain detailed information that allows candidates to appreciate the format and requirements of each OSCE. Each question features instructions to candidate, actor, and examiner, so candidates can practise in groups and recreate OSCE stations. MCEM-style marking sheets ensure that candidates have a good understanding of the standard that is required by the College. Complete and up-to-date, this book will give trainees a realistic and comprehensive preparation for the MCEM Part C.

MRCEM Part C: 125 OSCE Stations, Second Edition mirrors the exam syllabus and each of the OSCE stations is not only mapped to the relevant curriculum code(s) but also features a pie chart that highlights the competencies being tested. The stations follow a broadly consistent structure (introduction, scenario, mark sheet and instructions to actor) designed to allow candidates to work through each exam station under exam conditions, either individually or in a group.

This is the only book that MCEM candidates will need to pass the MCEM Part B exam. This revision guide is framed around the most recent CEM syllabus, focusing on all the components of the exam. Each section of the book is tailored to match different elements of the syllabus, allowing candidates to revise efficiently and comprehensively. This concise revision tool is completely up-to-date, reflecting the latest developments in the examination. High quality artwork and a bullet-point style help candidates to absorb information quickly. It also includes over 35 short answer questions enabling candidates to gain invaluable exam practice. Exam tips are included throughout the book to help candidates improve their exam technique.

A concise revision guide for one of the most difficult parts of the MCEM examination, covering the anatomy and basic sciences that will be tested in the Part A paper. Presented in note form, and with high quality explanatory diagrams, this book will equip candidates with the knowledge needed to pass the examination.

Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts, missing data, measurement errors, censoring, and outliers. For each class of mixed effects model, the author reviews the corresponding class of regression model for cross-sectional data. An overview of general models and methods, along with motivating examples After presenting real data examples and outlining general approaches to the analysis of longitudinal/clustered data and incomplete data, the book introduces linear mixed effects (LME) models, generalized linear mixed models (GLMMs), nonlinear mixed effects (NLME) models, and semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values, measurement errors, censoring, and outliers. Self-contained coverage of specific topics Subsequent chapters delve more deeply into missing data problems, covariate measurement errors, and censored responses in mixed effects models. Focusing on incomplete data, the book also covers survival and frailty models, joint models of survival and longitudinal data, robust methods for mixed effects models, marginal generalized estimating equation (GEE) models for longitudinal or clustered data, and Bayesian methods for mixed effects models. Background material In the appendix, the author provides background information, such as likelihood theory, the Gibbs sampler, rejection and importance sampling methods, numerical integration methods, optimization methods, bootstrap, and matrix algebra. Failure to properly address missing data, measurement errors, and other issues in statistical analyses can lead to severely biased or misleading results. This book explores the biases that arise when naïve methods are used and shows which approaches should be used to achieve accurate results in longitudinal data analysis.