## A Curated List of Our Postings on Technical Topics – Your One-Stop Shop for Methodology

*Updated August 20, 2015.*

**Random Assignment**

Allocating treatment and control with multiple applications per applicant and ranked choices [1]

Is optimization just re-randomization redux? Thoughts on the "don't randomize, optimize" papers [2]

Be an optimista, not a randomista, when you have small samples [3]

Tips for randomization in the wild: adding a waitlist [4]

How to randomize in the field [5]

Stratified randomization and the FIFA world cup [6]

Doing stratified randomization with uneven numbers in the Strata [7]

How to randomize using many baseline variables [8]

Public randomization ceremonies [9]

Designing experiments to measure spillover effects [10]

Mechanism experiments [11] and opening up the black box [12]

Sample weights and RCT design [13]

**Pre-analysis plans and reporting**

Pre-registration of studies to avoid fishing and allow transparent discovery [14]

A joint test of orthogonality when testing for baseline balance [15]

A pre-analysis plan check-list [16]

The New Trial Registries [17]

What isn’t reported in impact evaluations but maybe should be [18]

Randomization checks: testing for joint orthogonality [15]

An addendum to pre-analysis plans: pre-specifying when not to use data [19]

**Propensity Score Matching**

Guido Imbens on clustering standard errors with matching [20]

Testing different matching estimators as applied to job training programs [21]

The covariate balanced propensity score [22]

**Difference-in-Differences**

The often unspoken assumptions behind diff-in-diff [23]

**Regression Discontinuity**

Curves in all the wrong places: Gelman and Imbens on why not to use higher-order polynomials in RD [24]

Regression discontinuity with an implicit index [25]

**Other Evaluation Methods**

Evaluating an Argentine tourism policy using synthetic controls: tan linda que enamora? [26]

Impact as narrative [27]

The synthetic control method [28], as applied to regulatory reforms

Using spatial variation [29] in program performance to identify impacts

Small n impact evaluation methods [30]

Can we trust shoestring evaluations? [31]

**Analysis**

Another reason to prefer Ancova: dealing with measurement changes between baseline and follow-up [32]

Endogenous stratification: the surprisingly easy way to bias your heterogeneous treatment effects and what to do instead [33]

Why is difference-in-difference estimation still so popular in experimental analysis? [34]

Regression adjustment in randomized experiments (part one [35], part two [36])

When to use survey weights [37] in analysis

Adjustments for multiple hypothesis testing [38]

Bounding approaches to deal with attrition [39]

Linear probability models versus probits [40]

Dealing with multiple lotteries [41]

Estimating standard errors with small clusters (part one [42], part two [43])

Decomposition methods [44]

Estimation of treatment effects with incomplete compliance [45]

**Power Calculations and Improving Power**

Should I work with only a subsample of my control group if I have take-up problems? [46]

Power calculations: what software should I use? [47]

Does the intra-cluster correlation matter for power calculations if I am going to cluster my standard errors? [48]

Power calculations for propensity score matching [49]

Power calculations 101: dealing with incomplete take-up [50]

Collecting more rounds of data to boost power [51]

Improving power in small samples [52]

Power calculations for regression discontinuity (part 1 [53], part 2 [54], part 3 [55])

**On External Validity**

Getting beyond the mirage of external validity [56]

All those external validity issues with impacts? They apply to costs too [57]

External validity as seen from other quantitative social sciences and the gaps in our practices [58]

Towards a more systematic approach to external validity: understanding site selection bias [59]

Weighting for external validity [60]

Will that successful intervention over there get results here? [61]

Learn to live without external validity [62]

Why the external validity of regression estimates can be less than you think [63]

Why similarity is the wrong concept for external validity [64]

A rant on the external validity double standard [65]

**Jargony Terms in Impact Evaluations**

A proposed taxonomy of behavioral responses to evaluation [66]

Quantifying the Hawthorne effect [67]

The Hawthorne Effect [68]

The John Henry Effect [69]

Placebo effects [70]

Clinical Equipoise [71]

**Stata Tricks**

Generating regression and summary statistics tables in Stata [72]

Graphing impacts with Standard Error Bars [73]

Calculating the intra-cluster correlation [74]

Generating regression and summary statistics tables in Stata: A checklist and code [72]

**Replication**

Worm wars: the anthology [75]

Worm wars: a review of the reanalysis of the Miguel and Kremer deworming study [76]

Response to Brown and Wood's response [77]

Brown and Woods response on "how scientific are scientific replications" [78]

how scientific are scientific replications? [79]

**Systematic reviews and meta-analysis**

how systematic is that systematic review? The case of learning outcomes [80]

How standard is a standard deviation? A cautionary note on using SDs to compare across impact evaluations [81]

should we give up on SDs for measuring effect size? [82]

What do 600 papers on 20 types of interventions tell us about what types of interventions generalize? [83]

- Tags:
- Difference-in-difference [84]
- statistical power [85]
- propensity score [86]
- external validity [87]
- randomization [88]
- Life the Universe and Everything [89]