Multilevel Modelling - 11th May
This one-day course begins with a description of some examples where multilevel models are useful in statistical analysis and some examples of multilevel populations. We then cover the basic theory of multilevel models and a brief introduction to software that has been written specifically for fitting multilevel models: MLwiN. No prior knowledge of multilevel modelling is assumed. Participants will get some experience of using MLwiN software.
Demographic Concepts and Methods - 14-15th May
This course is delivered over two consecutive days and is aimed at those with no demographic training. The focus will be on the basic components of demographic change through measures and data sources to calculate and illustrate population structure, fertility, mortality and migration. Thus included are population pyramids, sex ratios, dependency ratios and fertility rates. The calculation of age-sex standardised ratios are also included in the course.
Population Estimating and Forecasting - 16th May This course is aimed at those with a working knowledge of demography but having a need to expand this into the use of estimation and forecasting. The morning sessions will focus on relatively simple methods of estimating subnational populations. We then move onto more complex cohort-component methods. In the afternoon we learn how to forecast future populations and experiment with varying our assumptions about future demographic trends.
Demographic Forecasting with POPGROUP - 17-18th May
The course introduces the standard methods of forecasting population, households and the labour force, each with age and sex detail, through use of the POPGROUP software. Most time is spent on the more complex tasks of preparing population forecasts. The focus is on sub-national forecasts for districts of England and Wales, but the principles transfer directly to national forecasts, to sub-national forecasts of other areas, and to social or ethnic groups, each of which are discussed. The emphasis is on hands-on learning through practical sessions that take the participants through the preparation of inputs, running a forecast, analysing results, and adjusting forecasts to implement a range of scenarios or assumptions.
Statistics for Small Samples - 29th May
The course aims to cover bivariate statistical tests for a variety of situation. The basic material of t-test is enriched by adding methods for the comparison of the distribution (or a mean) in cases where the variable is not normally distributed The participants learn to critically assess the validity of claims to statistical inference (from sample to population) in small-N and medium-N situations. Helpful examples are provided in the form of primary survey data from the Young Lives Programme data on care-givers of children born in the year 2000 in four countries, and from a large employment dataset.
Causal Modelling in Stata - 6th June
Many analysts move from simple regression to more complex causal modelling as their professional life develops. This course introduces basic techniques that are helpful for making statistical inferences in the intermediate level models: using a ‘long’ format panel data set; applying regression to panel data; drawing out causal interpretations. The course will also cover some causal concepts, describe statistical approaches to causal inference, give worked examples of regression models, and give hands-on experience in applied causal analysis using STATA.