Stata work we help with
Stata sits between a point-and-click package and a programming language. Most users start with the menus and quickly realise that serious work happens in do-files. We support both, but always steer towards code because it is the only way to make an analysis reproducible.
Typical requests include:
- Data management.
import,mergewith sensible use of the_mergevariable,append,reshapebetween wide and long,egenfor group statistics, and labelling withlabel define. - Exploring data.
summarize, detailfor means, medians and percentiles,tabulateandtabstat, histograms and scatter plots withtwoway. - Regression.
regresswith robust or clustered standard errors,logitandprobit,ologitfor ordered outcomes, andmarginswithmarginsplotto interpret them. - Panel and time-series data.
xtset,xtregwith fixed or random effects, the Hausman test,tssetand lag operators. - Causal designs. Instrumental variables with
ivregress, difference-in-differences, and survey-weighted estimation usingsvyset.
Common Stata mistakes and how we fix them
| Symptom | Likely cause |
|---|---|
| Sample size drops sharply in a regression | Listwise deletion from missing values in one covariate; check with misstable summarize |
| Merge creates duplicate rows | A 1:1 merge on a key that is not unique; the correct form may be m:1, which isid or duplicates report will reveal |
| Logit coefficients interpreted as probabilities | Coefficients are log-odds; use the or option for odds ratios or margins for probabilities |
| Strange results after recoding | Stata stores missing as a very large number, so if x > 50 silently includes missing values |
| Standard errors seem too small | Observations clustered within firms, schools or countries but not declared with vce(cluster id) |
Spotting these early is often the most valuable thing a second pair of eyes can do.
How we work on your do-file
We start by running your existing code, if you have any, against your data so we see exactly what you see. Then we restructure it into a clear sequence: setup and logging, data cleaning, variable construction, analysis and output. Each block gets comments that explain why, not just what. If the project feeds into a thesis, we align the work with our dissertation statistics help so the analysis plan and the code tell the same story.
Sessions are on screen-share with Stata open on your machine, so you type the commands yourself while we explain. If you are still deciding between packages, our R help and support for SAS, EViews and other software cover the alternatives.
Tables, graphs and output that survive revision
A frequent request is turning a screen full of regression output into a table fit for a thesis or journal. We set this up in code so it updates automatically when the model changes, using community commands such as esttab from the estout package or, in Stata 17 and later, the built-in etable and collect system. Graphs follow the same principle: scatter plots, histograms and coefficient plots are written as twoway or coefplot commands with a consistent scheme, then exported with graph export. Edits made in the Graph Editor are lost the next time you rerun the do-file, so we save them as code wherever possible.
We also add a log using line so every run leaves a dated record, which makes it simple to answer the inevitable question about which version of the results went into which draft.
Getting started
Send a short description of the project, your Stata version and edition, any do-files you already have, and your data in .dta, CSV or Excel format along with a codebook. Mention any deadlines from your programme or journal. We reply with a free quote within a few hours and can usually schedule a first session within days.
Like all our analysis work, the goal is that you finish able to explain every line. A do-file you understand is far more useful at a defense or in a replication package than one you merely received.
What you get
- A commented, runnable do-file from raw data to final tables
- Data management steps documented, including merges, reshapes and variable construction
- Model output with diagnostics and a plain-language interpretation
- Publication-style regression tables exported with esttab or Stata's collect and etable commands
- Graphs produced in code, not edited by hand, so they can be regenerated
- A live session to walk through the code with you
What we don't do
- For graded Stata problem sets we explain the commands and check your code rather than writing answers for submission
- We cannot provide Stata licences, though we can advise on which edition you need
How it works
Describe your project
Level, deadline and what you need help with.
Agree a written scope
What's included, the price and the timeline.
Work in stages
Check-ins so you can steer the work.
Review and ask
Explanations and follow-up questions included.