UCL ICH Statistics Courses

Diary Dates

June

6 Survival analysis
12 Intro to R - FULL
19 Sample size

July

3-4 Missing data (** 4 optional)
9-11 Intro to statistics with R - FULL
22-26 Intro to stats & research methods - No GradSchool places left
31 SPSS - FULL

September

20 Data linkage

Analysing a 2x2 table  

Outline of workshop:

When data is collected from 2 binary responses on the same individuals or items then the data may be displayed as a 2x2 table. It is often of interest to determine whether there is some form of association between the two variables. The chi-squared test is most commonly used by researchers to do this. However, there are many other statistics that may be applied to a 2x2 table to provide more useful information. The aim of this workshop is to guide the researcher through alternatives to decide on the most appropriate investigation of their data. publish now

Bayesian Analysis; Introduction to

Outline of workshop:

This course aims to familiarise the audience with the concepts of Bayesian analysis. Its basic principles (e.g. Bayes theorem) will be explained and how these are embedded in the medical science and research. By the end of this workshop, students should be able to understand and critically evaluate published research that has used Bayesian analysis as well as be confident to implement Bayesian concepts in their own research.

Critical Appraisal

Outline of workshop:

The ability to critically appraise published research is a key skill for all researchers. In this workshop we discuss the importance of defining the research question and the collection and evaluation of research to answer the question as posed. Checklists are introduced and their implementation in the evaluation of individual papers illustrated. Participants will be given papers to evaluate in a practical session.

Data Linkage; Introduction to  

Outline of workshop:

This short course is designed to give participants a practical introduction to data linkage and is aimed at researchers either intending to use data linkage themselves or to analyse linked data. Examples of the uses of data linkage, data preparation, methods for linkage (including deterministic and probabilistic approaches) and issues for the analysis of linked data are covered. The main focus of this course will be health data, although the concepts will apply to many other areas.

This course includes a practical example involving data to be linked, to enable participants to put theory into practice. Participants will need to bring their own laptops with software Link Plus installed on them. This is developed by Centers for Disease Control and Prevention (CDC) and is freely available from  http://www.cdc.gov/cancer/npcr/tools/registryplus/lp_tech_info.htm

On completing the course, participants will

• Understand the background and theory of data linkage methods
• Perform deterministic and probabilistic linkage
• Evaluate the success of data linkage
• Appropriately report analysis based on linked data

Dealing with Missing Data; Introduction to  

Outline of workshop:

The ability to critically appraise published research is a key skill for all researchers. In this workshop we discuss the importance of defining the research question and the collection and evaluation of research to answer the question as posed. Checklists are introduced and their implementation in the evaluation of individual papers illustrated. Participants will be given papers to evaluate in a practical session.

Logistic Regression; Introduction to  

Outline of workshop:

Binary (proportion/percentages) outcomes are common in medical and scientific research. This course covers:

- odds ratios as a means of comparing binary outcomes between two groups
- how logistic regression allows for other factors within this comparison
- the basics of logistic regression
- model selection and goodness-of-fit with examples from a variety of applications
- interpretation of SPSS output
- discussion of extension to the analysis of ordinal outcomes

Multilevel data analysis with R; Gentle introduction to  

Outline of workshop:

The aim of this workshop is to provide an introduction to multilevel research design and data analysis using the R statistical environment. This workshop will enable participants to

(a) develop an understanding of multilevel research and appreciate the potential of multilevel modelling for theory development 

(b) better understand published research that uses multilevel techniques

(c) use the R statistical environment to analyse their own multilevel models

Research increasingly requires more complex designs with more data, often collected from individuals in different social contexts or backgrounds. This creates (a) a methodological challenge because such data violate basic assumptions of linear regression, and  (b) an opportunity to understand how factors at different levels of analysis (e.g. school, organization, etc) can impact on individuals. This workshop will introduce participants to methods, techniques and software that can be used to address the challenges and take advantage of the opportunities that multilevel approaches offer.  

The workshop will be organized in three parts, which will introduce users to multilevel modelling using R and some of the available R packages.  Each of these sections will begin with a short presentation on the background theory and assumptions and will be followed by practical examples that participants will have an opportunity to try for themselves.  

The workshop is intended for anyone interested in data analysis of multilevel data (e.g. school-classroom-student or hospital-ward-patient). Participants are not required to have any prior knowledge of multilevel modelling but some knowledge of basic statistical techniques (primarily linear regression) and the R statistical environment is required. 

Quantile regression; Introduction to  

Outline of workshop:

There are many types of regression analysis. The most known is mean regression, which includes Gaussian, binomial, and Poisson regression. This is an introductory course to quantile regression, where the target of the inference are the quantiles (e.g., the median or the 95th percentile) of the outcome distribution. Quantile regression, as opposed to mean regression, is distribution-free and robust to outliers.

Topics include:
- brief recap of basics in probability (random variables, measurement scales, summary statistics)
- recall of mean regression
- quantiles of a distribution
- quantile regression for continuous distributions: estimation, inference and model assessment
- interquantile range regression: analysis of heteroscedasticity (i.e., nonconstant variance) and shape of a distribution
- Stata commands for quantile regression and interpretation of output
- R commands for quantile regression 

R for Statistical Analysis; Introduction to  

Outline of workshop:

This course is aimed to researchers that want to learn how to use the statistical software R in order to conduct statistical analysis. Delegates will be expected to bring their own laptops with R installed (step-by-step installation guidelines will be sent to all participants 2 weeks before the course). Moreover delegates will be expected to have a basic understanding of common statistical tests and concepts as these will not be taught during this workshop. The topics covered using R will include:

- Input of data sets
- Summary measures
- Graphical displays
- Statistical tests (parametric and non-parametric)
- Add-ons and packages in R
- Help in R And time permitting (notes will be given regardless):

- Regression analysis
- Sample size and power calculations

Regression Analysis; Introduction to 

Outline of workshop:

This workshop introduces various forms of regression and their usage:

- multiple linear regression (discussed in detail)
- interpretation of SPSS outputs
- choice of model
- assessing adequacy of model fit
- identification of outliers 

The course will be of use to users of alternative statistical packages as the issues covered are of generally applicable.

Research Methods and Statistics; Introduction to  

Outline of workshop:

This is a basic course in medical statistics that covers the following topics:

- introduction, types of data and graphical displays
- summarising data
- reliability and validity
- confidence intervals and p-values
- hypothesis testing
- proportions
- non-parametric tests
- categoric data
- confounding factors

Sample size estimation and power calculations  

Outline of workshop:

The concepts of sample size estimation are introduced. Both precision and the traditional power calculations are covered. Sample size estimation for:

- means
- proportions/ percentages
- time to event data
- rates
- measures of agreement
- centiles Excel sheets to perform the calculations are provided on a take-home CD. 

This workshop will take place in a computer room where applicants will have the opportunity to use the computers provided in order to gain full benefit from the workshop practical exercises that utilize the excel sheets.

SPSS; Introduction to

Outline of workshop:

This is a practical course that will introduce delegates to SPSS and its uses for statistical analysis through hands-on experience. The course is suitable for individuals who are new to SPSS or who feel they would benefit from a refresher course, and will cover the following topics:

- Getting started with SPSS files
- Data entry: manually and from excel
- Editing and organising datasets
- SPSS options and functions
- Descriptive statistics
- Graphical displays
- Parametric significance tests
- Nonparametric significance tests

The course will take place in a cluster room, with access to a computer and version 21 of SPSS throughout the day. Delegates are welcome to bring their own laptops if preferred, but everyone wishing to bring their own computer should ensure the software is licenced before attending. Where possible, we recommend using a recent version of SPSS (e.g., 19-21) for maximum compatibility with the notes provided during the course.

Statistics with R; Introduction to  

Outline of workshop:

This course is aimed at professionals who want to be able to understand the fundamental principles of statistics and to be able to conduct their own analyses. The latter will be explored via the use of the free statistical software R. Topics that will be covered are as follows:

- overview of quantitative research study designs
- types of data
- graphical displays
- summarising data
- confidence intervals
- hypothesis testing (parametric and non-parametric tests)
- p-values
- analysis of variance
- regression analysis (time permitting – notes will be provided regardless) 

Delegates will be expected to bring their own laptops with R installed (step-by-step installation guidelines will be sent to all participants 2 weeks before the course).

This course is a combination of the Introduction to Research Methods and Statistics and Introduction to R for Statistical analysis courses. Individuals are advised to attend either this 3 day course or the 5 day and 1 day courses.

Survival Analysis; Introduction to  

Outline of workshop:

This workshop gives an introduction to time to event (survival) data for the non-statistician, covering:

- use of Kaplan-Meier plots
- life tables
- Cox regression analyses
- interpretation of SPSS output

The list that follows includes topics that can potentially be organised depending on demand:

• Analysis of crossover trials
• Analysis of longitudinal data
• Clustered data
• Construction and use of centile ranges
• Interim analysis
• Reliability and measurement error

If you wish to attend a course on one of the topics above and there is no suitable currently advertised workshop then please contact the Statistics Courses Team at ich.statscou@ucl.ac.uk to express your interest and to be put on an alert list for when a course/place becomes available.

Suggestions for other courses may be sent to ich.statscou@ucl.ac.uk

Courses are designed for health professionals who require an understanding of research methodology and statistical analyses. This will allow them to interpret published research and/or undertake their own research studies.

More advanced courses aimed at statisticians can be found on the

• RSS Professional Development Centre

No prior statistical knowledge is assumed for the basic course ('Introduction to research methodology and statistics'). More advanced courses assume that the basics are understood. All courses use practical examples from commonly used peer reviewed journals and examples incorporating real datasets.

Extensive notes are provided for all courses. Lecture sessions are interspersed with practical examples to ensure that everyone has understood the principles. A relatively informal learning atmosphere is encouraged, where participants are not afraid to question or voice any confusion.

There are two course co-ordinators who are both present at all courses and help is always on hand for those who are unsure of anything (visit the 'About us' tab for more details).

Statistical Support Service (SSS)

Based within the Centre for Paediatric Epidemiology and Biostatistics, SSS is available to staff from ICH and GOSH and provides statistical support to researchers contributing to the maintenance of high standards of published research within the joint institution. To find out more about this service please visit the following link - SSS.

Qualification

The basic course qualifies for 15 CPD points and can also qualify as an MSc module if the examination and additional reading are undertaken. Other courses qualify for student log-book points under the UCL student scheme. Further details can be obtained on request.

Who are we?

The statistics courses are run by Dr Angie Wade, Senior Lecturer in Biostatistics and Miss Eirini Koutoumanou, Teaching Fellow and Miss Vicki Adlridge, Teaching Fellow. Based within the UCL Institute of Child Health (ICH) and Great Ormond Street Hospital (GOSH), we run a variety of higher degree and other courses for non-statisticians aimed primarily at those within paediatrics and allied fields.

Who are our guest lecturers?

Geraci, Marco

Harron, Katie

Michaelides, George

Contact us

Website: www.ucl.ac.uk/stats-courses

Via email on: ich.statscou@ucl.ac.uk

Via phone:

• General/payment queries - Call us on: +44 (0) 2079052340
• Course-specific queries - Call us on: +44 (0) 77 30405 980

Via post: The Statistics Courses Team, ICH, 30 Guilford Street, London, WC1N 1EH

Where are we based?

All courses are based within ICH and GOSH. The nearest underground station is Russell Square on the Piccadilly line. Also Holborn, Euston and Kings Cross stations are all within easy walking distance.

Visitors to the Institute of Child Health

The Centre for Paediatric Epidemiology and Biostatistics at the Institute of Child Health and Great Ormond Street Hospital welcomes visitors to take part in all our teaching activities.

Visitors are responsible for securing their own accommodation. If accommodation is required you must secure it before arrival and fund all of your own living expenses independently. Please visit the following link for a list of places to stay in the local area: Information about accommodation for visitors (Word document, 48KB) or visit the UCL website for additional hotels nearby.

• Guilford street