Preface
1
Poverty and measurement theory principles
1.1
The Concept of Poverty
1.2
Theoretical dimensions of poverty
1.3
The measurement of poverty and its challenges
1.3.1
Challenges in selection of dimensions, contents, cut offs and weights
1.3.2
Challenges in aggregation and identification of the poor
1.4
The poor and the not poor: The poverty line
1.5
A brief on multidimensional poverty measurement
2
Poverty and measurement theory: A statistical framework
2.1
Workflow in poverty measurement: A falsifiable framework
2.2
Identification of the sampling space
2.3
Selection of dimensions and indicators
2.4
Aggregation and weighting
2.4.1
Splitting the population into meaningful groups
2.5
Measurement theory as an statistical framework
2.6
Poverty and error in measurement
2.7
Measurement model for poverty
2.8
Blueprints and poverty measurement models
2.9
Measurement theory and principles
2.9.1
Origins of measurement theory
3
Reliability in poverty measurement
3.1
Intuition to the concept of reliability
3.2
Reliability theory
3.3
Statistical measures of reliability
3.4
Item-level reliability and weighting
3.5
Estimation of Reliability
3.5.1
Overall reliability
3.5.2
Exploratory (non-model based) estimation of overall reliability
3.5.3
Model-based estimation of overall reliability
3.5.4
Overall reliability and population orderings
3.5.5
Item-level reliability
3.6
Multidimensional item-reliability evaluation
3.6.1
Item-reliability and monotonicity
3.7
Real data example
3.7.1
Overall reliability
3.7.2
Item-level reliability
4
Validity in poverty measurement
4.1
Intuition to the concept of validity
4.2
Theory of validity
4.3
Methods for the analysis validity
4.3.1
Criterion validity
4.3.2
Construct validity
4.4
Validity assessment
4.4.1
Criterion Validity
4.4.2
Construct Validity
4.4.3
A joint assessment: Criterion and construct validity
4.4.4
Real-data example
5
Comparability in poverty measurement
5.1
Measurement invariance
5.2
Introduction to key aspects of measurement invariance
5.3
Methods for the assessment of Measurement Invariance
5.3.1
Multiple Group Factor Analysis
5.3.2
The alignment method
5.4
Real-data analysis of Measurement Invariance
6
Scale equating and linking
6.1
Intuition to scale equating
6.2
Theory of scale equating [#Theoryequating]
6.2.1
Workflow in scale equating
6.2.2
Theory of IRT scale equating
6.3
Data and designs in test equating
6.3.1
Single group design
6.3.2
Equivalent groups design
6.3.3
Non Equivalent Groups with Anchor test Design
6.3.4
Non Equivalent Groups with Covariates Design
6.4
Example of IRT equating (NEAT design) with simulated data in R
6.5
Real-data example
6.5.1
Step 1: Finding the anchors. MI Analysis
6.5.2
Step 2: Extract IRT parameters for each of 10 indices
6.5.3
Step 3: Estimating the constants for equating
6.5.4
Step 4: Applying the constants and obtaning equated scores
6.5.5
Finding equated poverty lines
7
Identifying the poor group
7.1
The poverty line
7.2
Perspectives on the poverty line: Union and intersection approaches
7.3
The human rights-based approach
7.4
The UBN weighted approach
7.5
The partially-weighted approach
7.6
The Bristol Optimal approach
7.7
Example with simulated data
7.8
Real-data analysis
8
Final thoughts
8.1
The future of data production in multidimensional poverty measurement
8.2
Advanced topics in multidimensional poverty measurement
9
References
Multidimensional poverty measurement: A statistical approach with applications
Chapter 8
Final thoughts
8.1
The future of data production in multidimensional poverty measurement
8.2
Advanced topics in multidimensional poverty measurement