503
edits
Changes
mLine 51:
Line 51: − !Title + − + − + − + Line 67:
Line 67: + + + + + − + − + − + Line 78:
Line 83: + + + + + − + − + − + − Line 90:
Line 99: + + + + + − + − + − + − − +
no edit summary
{| class="wikitable"
{| class="wikitable"
|+
|+
!Date
!Date
!Time
!Description
!Description
!Language
!Language
!Agenda and Materials
!Agenda and Materials
|-
|-
|''Fundamental concepts of quantitative impact assessment''
|'''March 19'''
|<nowiki>March 19 | </nowiki>9am-12pm (ET)
|9am-12pm (ET)
|''Fundamentals'' will provide a comprehensive overview of QIA concepts. Participants will learn the difference between program outcomes and program impacts, and be introduced to the common approaches to QIA (such as difference-in-differences, discontinuity estimators, and more). This session will also offer a detailed overview of randomized controlled experiments – the gold standard of QIA.
|''Fundamentals'' provides a comprehensive overview of QIA concepts. Participants will learn the difference between program outcomes and program impacts, and be introduced to the common approaches to QIA (such as difference-in-differences, discontinuity estimators, and more). This session also offers a detailed overview of randomized controlled experiments – the gold standard of QIA.
|English with bilingual materials
|English with bilingual materials
|Session 1 - Agenda and Materials
|Session 1 - Agenda and Materials
{| class="wikitable"
{| class="wikitable"
|+
|+
!Date
!Time
!Description
!Language
!Agenda and Materials
|-
|-
|''Leveraging data for impact analysis''
|'''March 21'''
|<nowiki>March 21 | </nowiki>9am-12pm (ET)
|9am-12pm (ET)
|''Data'' will provide an overview of the data environments available through Statistics Canada. Participants will learn about performing custom tabulations and multivariate analysis, with specific emphasis on the availability of gender and diversity data and Quality of Life data. This session will explain how to access existing microdata and overcome data gaps.
|''Data'' provides an overview of the data environments available through Statistics Canada. Participants will learn about performing custom tabulations and multivariate analysis, with specific emphasis on the availability of gender and diversity data and Quality of Life data. This session explains how to access existing microdata and overcome data gaps.
|English with bilingual materials
|English with bilingual materials
|Session 2 - Agenda and Materials
|Session 2 - Agenda and Materials
{| class="wikitable"
{| class="wikitable"
|+
|+
!Date
!Time
!Description
!Language
!Agenda and Materials
|-
|-
|''Case Studies I: Applying QIA methods to evaluate program performance and impact''
|'''March 26'''
|<nowiki>March 26 | </nowiki>
|9am-12pm (ET)
9am-12pm (ET)
|''Case Studies I'' focuses on three real-life examples of QIA methods being applied to evaluate program performance and impact. These case studies primarily leverage social data. The methods covered are (1) empirical density design, (2) hierarchical linear modelling, and (3) propensity score matching and difference-in-differences.
|''Case Studies I'' will focus on three real-life examples of QIA methods being applied to evaluate program performance and impact. These case studies primarily leverage social data. The methods covered are (1) empirical density design, (2) hierarchical linear modelling, and (3) propensity score matching and difference-in-differences.
|English with bilingual materials
|English with bilingual materials
|Session 3 - Agenda and Materials
|Session 3 - Agenda and Materials
{| class="wikitable"
{| class="wikitable"
|+
|+
!Date
!Time
!Description
!Language
!Agenda and Materials
|-
|-
|''Case Studies II: Applying QIA methods to evaluate program performance and impact''
|'''March 28'''
|<nowiki>March 28 | </nowiki>
|9am-12pm (ET)
9am-12pm (ET)
|''Case Studies II'' also focuses on three real-life examples of QIA methods being applied to evaluate program performance and impact. These case studies primarily leverage business microdata. The methods covered are (1) propensity score matching and entropy balancing, (2) matching difference-in-differences, and (3) modified causal forest.
|''Case Studies II'' will also focus on three real-life examples of QIA methods being applied to evaluate program performance and impact. These case studies primarily leverage business microdata. The methods covered are (1) propensity score matching and entropy balancing, (2) matching difference-in-differences, and (3) modified causal forest.
|English with bilingual materials
|English with bilingual materials
|Session 3 - Agenda and Materials
|Session 4 - Agenda and Materials
|}
|}