CASS Course 2012

Posted on 2012/08/29. Filed under: 綜合 |

Short course announcement:

How to Analyse Survey Data: Methods, Software and Applications. University of Southampton, 19-21 September

Instructors: Prof Danny Pfeffermann, Prof Patrick Sturgis, Dr Moshe Feder, Dr Dave Holmes, Dr Pedro Silva

Survey data are frequently used for analytic inference on statistical models holding for the population from which the sample is taken. Survey data differ, however, from other data sets in important aspects: the samples are selected with known selection probabilities, which allows using the distribution over all possible sample selections as the basis for inference; the selection probabilities may be related to the model outcome variable in which case the model holding for the sample is different from the target population model; survey data are almost inevitably subject to nonresponse, which again may distort the population model if the response propensity is associated with the outcome; the sample is often clustered, implying that observations in the same cluster are correlated.

In this course we shall discuss and illustrate these problems and consider alternative approaches to address them. Available and new computer programs used to implement these approaches will be discussed with examples, using simulated and real data sets. The course will include several lab sessions.

Target Audience: The course is aimed at social science researchers and statisticians at all career stages in the academic, government and private sectors who wish to obtain an understanding of a range of possible approaches for the analysis of complex survey data, and how to apply them.

Course Fee: £30 per day for UK-registered students.
£60 per day for staff from UK academic institutions (including research centres), ESRC funded researchers and UK registered charitable organisations and all other participants.

This course offers a reduced fee for all other participants (usually £220 per day) as it is funded by an ESRC grant No. RES-062-23-2316.

Further Information:

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