Merge pull request #96 from pymc-labs/glossary

Add more entries to the glossary

Author: drbenvincent

docs/glossary.md

@@ -2,16 +2,48 @@
 
 <div class="admonition note" name="html-admonition">
 <p class="title">Note:</p>
-Some of the definitions have been copied (or inspired by) various resources, including Reichardt (2019).
+Some of the definitions have been copied from (or inspired by) various resources, including Reichardt (2019).
 </div>
 
-**Change score analysis:** Statistical procedure where the dependent variable is the difference between the posttest and protest scores. Another term for 'differences in differences'.
+**Average treatment effect (ATE):** The average treatement effect across all units.
 
-**Difference in Differences:** Analysis where the treatment effect is estimated as a difference between treatment conditions in the differences between pre-treatment to post treatment observations.
+**Average treatment effect on the treated (ATT):** The average effect of the treatment on the units that recieved it. Also called Treatment on the treated.
+
+**Change score analysis:** A statistical procedure where the outcome variable is the difference between the posttest and protest scores.
+
+**Comparative interrupted time-series (CITS) design:** An interrupted time series design with added comparison time series observations.
+
+**Confound** Anything besides the treatment which varies across the treatment and control conditions.
+
+**Counterfactual:** A hypothetical outcome that could or will occur under specific hypothetical circumstances.
+
+**Difference in Differences (DID) analysis:** Analysis where the treatment effect is estimated as a difference between treatment conditions in the differences between pre-treatment to post treatment observations.
+
+**Interrupted time series (ITS) design:** A quasi-experimental design to estimate a treatment effect where a series of observations are collected before and after a treatment.
+
+**Non-equivalent group designs:** A quasi-experimental design where units are assigned to conditions non-randomly, and not according to a running variable (see Regression discontinuity design).
+
+**One-group posttest-only design:** A design where a single group is exposed to a treatment and assessed on an outcome measure. There is no pretest measure or comparison group.
+
+**Panel data:** Time series data collected on multiple units where the same units are observed at each time point.
+
+**Pretest-posttest design:** A quasi-experimental design where the treatment effect is estimated by comparing an outcome measure before and after treatment.
+
+**Quasi-experiment:** An empirical comparison used to estimate the effects of a treatment where units are not assigned to conditions at random.
+
+**Random assignment:** Where units are assigned to conditions at random.
+
+**Randomized experiment:** An emprical comparison used to estimate the effects of treatments where units are assigned to treatment conditions randomly.
 
 **Regression discontinuity design:** A quasi–experimental comparison to estimate a treatment effect where units are assigned to treatment conditions based on a cut-off score on a quantitative assignment variable (aka running variable).
 
+**Sharp regression discontinuity design:** A Regression discontinuity design where allocation to treatment or control is determined by a sharp threshold / step function.
+
 **Synthetic control method:** The synthetic control method is a statistical method used to evaluate the effect of an intervention in comparative case studies. It involves the construction of a weighted combination of groups used as controls, to which the treatment group is compared.
 
+**Treatment on the treated (TOT) effect:** The average effect of the treatment on the units that recieved it. Also called the average treatment effect on the treated (ATT).
+
+**Treatment effect:** The difference in outcomes between what happened after a treatment is implemented and what would have happened (see Counterfactual) if the treatment had not been implemented, assuming everything else had been the same.
+
 ## References
 * Reichardt, C. S. (2019). Quasi-experimentation: A guide to design and analysis. Guilford Publications.