The IASS is regularly offering a number of short courses and workshops at the bi-annual meetings of the IASS (and ISI) and in other events.

64th ISI World Statistics Congress – Ottawa – Short Courses Program at ISI 2023

A rich program of short courses will be held on July 14 and 15, 2023 at the University of Ottawa right before the 64th ISI World Statistics Congress. At least 4 courses are of interest to IASS members:
• An introduction to the theory and application of Small Area Estimation by Jean-François Beaumont (Statistics Canada) –1 day
• Statistical Data Privacy by Anne-Sophie Charest (Université Laval) and Jingchen (Monika) Hu (Vassar College) –2 days
• Graph Sampling by Li-Chun Zhang (University of Southampton/Statistics Norway) –1 day
• Statistical Data Integration by Jae-kwang Kim (Iowa State University) –1 day

More details have now been posted on the conference web page

Short Courses offered at the 63rd ISI World Statistics Congress, Virtual, 2021

Short Course Programme Schedule

6 May
Large-Scale Spatial Data Science
Instructors: Prof. Marc Genton, Dr. Huang Huang, Dr. Sameh Abdulah

10 May – 12 May
Quality of multisource statistics
Instructors: Dr. Arnout van Delden, Dr. Ton de Waal

17 May
Fraud Analytics
Instructor: Dr. Tahir Ekin

18 May – 19 May
Financial Accounts – Concepts, compilation and use
Instructors: Henning Ahnert, Pierre Sola, Maciej Anacki, Andreas Hertkorn

20 May – 21 May
Building technical editing and science communication skills for 21st Century
Instructors: Prof. Elena N. Naumova, Prof. Alessandro Fassò

25 May – 27 May
Introduction to Graph Sampling
Instructors: Prof. Li-Chun Zhang, Dr. Melike Oguz-Alper

28 May
An Introductory Course in Competing Risks
Instructor: Jacobo de Uña-Álvarez

31 May
Recurrent Event Analysis in R with the reReg package
Instructor: Dr. Sy Han (Steven) Chiou

1 June – 3 June
Spatial Statistical Learning
Instructors: Dr. Soutir Bandyopadhyay, Dr. William Kleiber, Dr. Douglas Nychka

4 June
Reshaping challenging data to produce insightful graphs – a quick start to using R tidyverse tools
Instructors: Prof. John Bailer, Assoc. Prof. Thomas Fisher

7 June – 9 June
Statistical Theory of Deep Learning
Instructor: Dr. Sophie Langer

10 June – 11 June
Statistical Disclosure Control: Past, Present and Future
Instructor: Prof. Natalie Shlomo

14 June – 15 June
Introduction to Machine Learning
Instructor: Prof. David Banks

16 June – 17 June
Data Science and Predictive Analytics (DSPA)
Instructor: Prof. Dr. Ivo D. Dinov

18 June
Bootstrap Methods and Permutation Tests
Instructor: Tim Hesterberg

21 June – 22 June
Basketball Data Analysis
Instructors: Prof. Marica Manisera, Prof. Paola Zuccolotto

23 June
Teaching Data Science
Instructors: Dr. Mine Çetinkaya-Rundel, Dr. Colin Rundel

24 June
Communicating health data: the COVID-19 experience — day 1
Instructors: Prof. Fulvia Mecatti, Prof. Clelia Di Serio

28 June
Precision medicine: A statistical perspective on estimating the best treatment strategy
Instructor: Dr. Erica E.M. Moodie

29 June – 30 June
Cure Models: Methods, Applications, and Implementation
Instructors: Dr. Yingwei Peng, Dr. Binbing Yu

1 July
Communicating health data: the COVID-19 experience — day 2
Instructors: Prof. Fulvia Mecatti, Prof. Clelia Di Serio

Short Courses offered at the 58th ISI World Statistics Congress, Dublin 2011.

Course 1. Introduction to Survey Sampling

Instructors: Steven Heeringa, University of Michigan Institute for Social Research; Colm O’Muircheartaigh, the University of Chicago and National Opinion Research Center (NORC).

Draft Description: The workshop is intended to provide an overview of principles of sample design selection and estimation. It will start from basic principles of sample design and selection beginning with simple random sampling, and build up to complex stratified multi-stage sample designs. It will cover the main sampling techniques and also discuss such issues as sampling frames and weighting. An introduction to variance estimation for complex sample designs will be presented at the end of the workshop.

Duration: Two days.

Course 2. Analysis of Complex Sample Survey Data

Instructors: Jay Breidt, Colorado State University; Kirk Wolter, NORC.

Draft Description: Estimation procedures appropriate for data collected under complex survey designs will be discussed. The first part of the course will cover estimation and variance estimation for standard statistics, such as means, ratios, domain totals, and the entries in two-way tables. The use of survey data for the estimation of the parameters of statistical models is the focus of the second part of the course. Emphasis will be placed on efficient estimation of the parameters of regression models.

Duration: Two days.

Course 3. Introduction to Survey Quality

Instructors: Paul Biemer, RTI International and the University of North Carolina—Chapel Hill; Lars Lyberg, Statistics Sweden.

Draft Description: The course spans a range of topics dealing with the quality of survey data. It begins with a discussion of dimensions of survey quality which include accuracy, relevance, timeliness, accessibility, and comparability. We describe an approach to maximizing survey quality in which total survey error is minimized subject to constraints on costs after accommodating the other quality dimensions. The major components of total survey error include: nonresponse error, frame error, measurement error, specification error, data processing error, and file preparation error. We describe a set of principles for evaluating these major error sources and for deploying survey resources optimally to reduce their effects on survey estimates – an approach embodied in the so-called total survey error paradigm. The TSE paradigm considers the origins of each error source (i.e., its root causes) and applies the most effective methods for reducing or controlling the errors under costs and quality constraints. Methods for evaluating survey error such as cognitive interviewing, pretesting, behavior coding, re-interview surveys and administrative records checks are also covered. The course reviews well-established as well as recently developed methods and concepts in the field. It also examines important issues that are still unresolved today and which are being actively pursued in the current survey methods literature. The course concludes with a discussion of the practical advise for designing and conducting surveys that consistently achieve near optimal levels of survey quality.

Duration: Two days.

Course 4. Web Survey Design

Instructor: Mick P. Couper, University of Michigan Institute for Social Research, and the Joint Program in Survey Methodology at the University of Maryland.

Description: The course will focus on the design of web survey instruments and procedures based on theories of human-computer interaction, interface design, and research on self-administered questionnaires and computer assisted interviewing. The course will cover various aspects of instrument design for Web surveys, including the appropriate use of widgets (e.g., radio buttons, check boxes) for Web surveys, general formatting and layout issues, movement through the instrument (action buttons, navigation, error messages), and so on. The course will draw on empirical results from experiments on alternative design approaches as well as practical experience in the design and implementation of web surveys. The course will not address the technical aspects of web survey implementation, such as hardware, software or programming. The course will also not focus on question wording or sampling issues for Web surveys. The course will have a strong practical emphasis, examining many different examples of good and bad design, with recommendations for best practice.

Duration: One day.

Course 5. Methods for Longitudinal Surveys

Instructor: Peter Lynn, Institute for Social and Economic Research (ISER) University of Essex

Draft Description: Introduce participants to issues which are specific to longitudinal and panel surveys, including topics in sample design, survey design, instrument design, weighting and imputation. The course would give an overview of the strengths and weaknesses of longitudinal surveys and an outline of key considerations in the design and implementation of such surveys.

Duration: one/ two days.

Course 6. Workshop on Editing and Imputation of Survey Data

Instructors: John Kovar, Eric Rancourt, and Jean-Francois Beaumont, Statistics Canada.

Draft Description: Surveys and censuses conducted by national statistical agencies, research institutes and other survey organizations suffer from various degrees of nonresponse even under ideal conditions. In order to try to alleviate the problems caused by nonresponse, editing and imputation methods are usually applied. Since the process of editing and imputation is time and resource intensive, care must be exercised in controlling the efficiency as well as the effectiveness of the methods. The aim of this short course is to introduce the students to methods of nonresponse prevention and the treatment of suspicious, inconsistent and missing responses. Evaluation of such methods and their impact on the survey outputs will be highlighted. Examples will be provided to illustrate the material presented.

Duration: One and half days.

Course 7. Business Survey Methods

Instructors: Mike Hidiroglou, and Wesley Yung, Statistics Canada

Draft Description: Business surveys are important sources of information for producing key economic indicators that monitor the economy over time and for constructing official statistics such as national accounts. While business surveys typically use simple sample designs they are not without their methodological challenges such as highly skewed and unstable populations, the quality of frame information and auxiliary data used in stratification, editing, imputation and estimation. This workshop will describe methods for designing business surveys and will cover topics such as building and maintaining a Business Register, sample design, data collection, outlier detection and treatment, imputing for total and/or partial non-response, weighting and estimation and use of administrative data.

Duration: Two days.

Short Courses offered at the 57th ISI World Statistics Congress, Durban 2009

  • Course 1: Business Survey Design
  • Course 2: Editing and Imputation of Survey Data
  • Course 3: Introduction to Survey Sampling
  • Course 4: Analysis of Complex Sample Survey Data
  • Course 5: Introduction to Survey Quality
  • Course 6: Small Area Estimation Methods, Applications and Practical Demonstration
  • Course 7: Seasonal Adjustment

Short Courses offered at the 56th ISI World Statistics Congress, Lisbon 2007

  • Course 1: Workshop on Survey Sampling, by Colm O’Muircheartaigh and Steven Heeringa. 33 participants.
  • Course 2: Variance Estimation in Complex Surveys, b: Wayne Fuller, Kirk Wolter, F. Jay Breidt, and Anthony An. 23 participants.
  • Course 3: Workshop on Editing and Imputation of Survey Data, b: John G. Kovar and Eric Rancourt. 31 participants.
  • Course 4: Introduction to Survey Quality, 20-22 August, by Paul Biemer and Lars Lyberg. 37 participants.
  • Course 5: Statistical Disclosure Control, 30-31 August, by Anco Hundepool, Eric Schulte Nordholt and Peter-Paul de Wolf. 11 participants.
  • Course 6: Design and Analysis of Repeated Surveys, by David Steel and Craig McLaren. 23 participants.

Short Courses offered at the 55th ISI World Statistics Congress, Sydney 2005

  • Course 1: Workshop on Survey Sampling, by Graham Kalton (Westat); Steven Heeringa (Survey Research Center, University of Michigan). 21 participants
  • Course 2: Variance Estimation in Complex Surveys, by Wayne Fuller (Iowa State University); Kirk Wolter (University of Chicago); F. Jay Breidt (Colorado State University); Anthony An (SAS Institute). 19 participants
  • Course 3: Workshop on Editing and Imputation of Survey Data, by John G. Kovar (Statistics Canada); Eric Rancourt (Statistics Canada). 42 participants
  • Course 4: Introduction to Survey Quality, by Paul Biemer (RTI International and University of North Carolina); Lars Lyberg (Statistics Sweden). 18 participants
  • Course 5: Statistical Disclosure Control, by Eric Schulte Nordholt (Statistics Netherlands); Peter-Paul de Wolf (Statistics Netherlands). 18 participants
  • Course 6: Design and Analysis of Repeated Surveys, b: David Steel (University of Wollongong); Craig McLaren (Australian Bureau of Statistics). 23 participants

Short Courses offered at the 54th ISI World Statistics Congress, Berlin 2003

  • Course 1: Workshop on Survey Sampling, by Graham Kalton (Westat) and Steven Heeringa (The Statistical Design Unit at the Survey Research Center, University of Michigan); 37 students registered for the course.
  • Course 2: Variance Estimation in Complex Surveys, by Wayne Fuller (Iowa State University), Kirk Wolter (NORC), F. Jay Breidt (Iowa State University), and Anthony An (SAS Institute); 28 students registered for the course.
  • Course 3: Introduction to Small Area Estimation, by J.N.K. Rao (Carleton University); 33 students registered for the course.
  • Course 4: Editing and Imputation of Survey Data, by John G. Kovar (Statistics Canada) and Eric Rancourt (Statistics Canada); 34 students registered for the course.
  • Course 5: Business Survey Methods, by Mike Hidiroglou (Statistics Canada) and David Binder (Statistics Canada); 30 students registered for the course.
  • Course 6: Designing the Optimal Questionnaire, by Edith de Leeuw (MethodikA/Utrecht University, The Netherlands) and Don Dillman (The Social and Economic Sciences Research Center, Washington State University; 34 students registered for the course.