Data are not only ubiquitous in society, but are increasingly complex both in size and dimensionality.  Meer

This Element develops uniting principles that constitute the qualitative and quantitative assumptions that form the basis for a quantitative relationship between constituent studies.  Meer

This Element introduces the basics of Bayesian regression modeling using modern computational tools and assumes that the reader has taken a basic statistics course and has seen Bayesian inference at the introductory level.  Meer

This Element introduces the basics of Bayesian regression modeling using modern computational tools and assumes that the reader has taken a basic statistics course and has seen Bayesian inference at the introductory level.  Meer

In this Element, the authors introduce Bayesian probability and inference for social science students and practitioners starting from the absolute beginning and walk readers steadily through the Element.  Meer

This Element discusses covers (i) the local randomization framework for RD analysis, (ii) the fuzzy RD design where compliance with treatment is imperfect, (iii) RD designs with discrete scores, and (iv) and multi-dimensional RD designs.  Meer

This Element develops uniting principles that constitute the qualitative and quantitative assumptions that form the basis for a quantitative relationship between constituent studies.  Meer

In this Element, the authors introduce Bayesian probability and inference for social science students and practitioners starting from the absolute beginning and walk readers steadily through the Element.  Meer

This Element discusses covers (i) the local randomization framework for RD analysis, (ii) the fuzzy RD design where compliance with treatment is imperfect, (iii) RD designs with discrete scores, and (iv) and multi-dimensional RD designs.  Meer