What We Can Help You With: A Detailed Breakdown
Our expertise covers the full spectrum of Stata’s capabilities. Below are the specific models, tasks, and analyses we frequently assist students with.
Data Management and Preparation
Importing Data: From Excel (.xls, .xlsx), CSV (.csv), text (.txt), and other formats.
Data Cleaning: Identifying and handling outliers, duplicates, and missing values (misstable).
Data Structuring: Merging (merge), appending (append), and reshaping data from wide to long format and vice-versa (reshape).
Variable Generation: Creating new variables from existing ones (generate, egen), including interactions, dummy variables, and logs.
Labeling: Properly labeling variables and values for clarity.
Descriptive Statistics and Data Visualization
Summary Statistics: Generating tables of means, standard deviations, and correlations (summarize, tabulate, correlate).
Table Creation: Creating publication-quality regression and summary tables using estout, outreg2, or tabout.
Graphing: Creating high-quality visualizations like scatter plots, line graphs, bar charts, and histograms (graph twoway, graph bar, histogram).
Econometric and Statistical Modeling
Linear Regression: Ordinary Least Squares (OLS) using regress.
Binary Choice Models: Logistic Regression (logit) and Probit Regression (probit).
Ordered & Multinomial Models: Ordered Logit/Probit (ologit/oprobit) and Multinomial Logit (mlogit).
Panel Data Analysis: Pooled OLS, Fixed Effects (xtreg, fe), and Random Effects (xtreg, re) models.
Advanced Panel Data: Dynamic Panel Data (Arellano-Bover/Blundell-Bond with xtabond2), and Hausman tests.
Time-Series Analysis: Setting time-series data (tsset), ARIMA models, Vector Autoregression (VAR), and unit root tests.
Instrumental Variables (IV): Two-Stage Least Squares (2SLS) using ivregress for endogeneity issues.
Other Advanced Models: Heckman selection models (heckman), treatment effects models (treatreg), and Difference-in-Differences (DiD).
Post-Estimation and Interpretation
Hypothesis Testing: Testing linear and non-linear combinations of coefficients (test, lincom).
Diagnostic Tests: Checking for heteroskedasticity, multicollinearity (vif), and autocorrelation.
Marginal Effects: Calculating and interpreting marginal effects after non-linear models (margins, marginsplot).
Interpreting Results: Explaining the meaning of your coefficients, p-values, R-squared, and overall model fit in the context of your research.
From Coursework to Dissertation: We've Got You Covered
We tailor our Stata help to your specific academic needs, ensuring you meet your deadlines and requirements.
Coursework & Assignments
Stuck on a problem set or a data analysis exercise? We can help you complete your assignment accurately and provide explanations so you understand the underlying concepts.Thesis & Dissertation Empirical Chapters
This is our specialty. We provide end-to-end support for your empirical chapter, including methodology design, data analysis, and writing up the results and interpretation.Replication Studies
Tasked with replicating the results of a published academic paper? We can help you write the do-file to reproduce the paper’s tables and figures, a common requirement in econometrics courses.
Stop Struggling with Stata. Start Getting Results.
Don’t let software challenges derail your research. Let our PhD-level experts handle the technical analysis, providing you with the accurate and well-documented results you need to excel.