At Ondezx, we help researchers choose the proper statistical methods and conduct each analysis properly using Stata, and interpret the results with confidence. We have experience in descriptive analysis, inferential statistics, multivariate analysis, structural equation modelling and time-to-event analysis in a variety of research areas. We offer end-to-end Data Analysis Using Stata support that enhances the quality and credibility of doctoral research, from data cleaning to model specification, assumption testing, interpretation of output and research reporting.
Once the analysis is completed, Ondezx focuses on turning the statistical findings into clear, research-ready outputs. We organise Stata results into structured tables and formats suitable for thesis chapters, research papers, and academic presentations. The final deliverables are aligned with the study requirements, helping researchers communicate their statistical findings clearly and maintain consistency between the analysis, results, and research documentation.
Well-prepared data is the first step to reliable analysis. Our experts can use a variety of sources to import your data, remove inconsistencies, recode variables, join files, handle missing values and outliers, and restructure data so that your research data is suitable for accurate statistical analysis in Stata.
We summarise your dataset with descriptive statistics, frequency distribution, cross-tabulations, graphical visualisations and exploratory techniques that assist in finding patterns before the more sophisticated statistical modelling.
We conduct relevant statistical analysis according to your research question, such as t-test, ANOVA, chi-square test, correlation analysis, and non-parametric analysis to substantiate your hypothesis with statistical evidence.
We design regression models to suit your research design needs and analysis needs. Linear and multiple regression
We support complex doctoral studies that require advanced econometric and statistical analysis. We apply methods such as instrumental variable estimation, difference-in-differences, propensity score matching, and regression discontinuity to examine causal relationships, treatment effects, policy impacts, and other research questions involving observational or non-randomised data.
We review the Stata output and explain the results in relation to your analysis. We identify the key findings, explain the direction and strength of relationships, interpret statistical significance and relevant estimates, and help convert the findings into clear academic write-ups.
We support you in developing the statistical content of your thesis chapters. We help structure the methodology, present the selected analytical methods, organise statistical tables and figures, and incorporate the analysis into the appropriate sections while following your university's formatting and reporting requirements.
We write customised Stata code and develop structured do-files for your research analysis. We create commands for data cleaning, variable transformation, statistical testing, model estimation, and result generation, with clear documentation to make the analysis organised, reproducible, and easy to review.
We provide one-on-one consultations tailored to your specific research needs. You can discuss your dataset, statistical methods, Stata procedures, model selection, and results directly with our experts and receive personalised guidance based on your study.
We have experience in complex statistical analysis beyond simply routine work and can help in the analysis of special problems in doctoral research in a variety of engineering, management, healthcare, social sciences, economics, and allied disciplines.
We cluster observations into meaningful groups using hierarchical and non-hierarchical methods, helping researchers uncover hidden patterns, customer segments, behavioral groups, and research typologies within large datasets.
Our experts also conduct network meta-analysis, which enables comparison of multiple interventions often needed in medical and healthcare research when there is both direct and indirect evidence from multiple studies.
Power and sample size analyses are performed to determine whether the study has sufficient power to detect meaningful effects, thereby strengthening the validity of the study design both before and after the study.
PCA is used to reduce the dimensionality of data, to find underlying components in it, to remove redundancy among variables, and to simplify the complex data set while still preserving the important data.
Our team applies suitable Stata time series commands such as ARIMA, VAR, unit root test, forecasting models or trend analysis for time series in longitudinal and economic research.
Analyzing the relationships between two variables with appropriate statistical methods to assess associations, to compare groups, and to provide evidence for hypothesis testing.
When there are several competing event outcomes, we use competing risk analysis in Stata to accurately estimate event probabilities and provide meaningful time-to-event interpretations.
We create confirmatory factor analysis models for questionnaire validation, to check for measurement construct validity and for model fit in advanced doctoral research and behavioural research.
Ondezx follows a clear, step-by-step process to turn research data into accurate statistical results using Stata, while keeping the analysis consistent with the study methodology and thesis requirements.
The research objectives, hypotheses, variables, methodology, and dataset are reviewed first. This helps establish what the data represents and what needs to be analysed.
The dataset is cleaned and organised before analysis. Missing values, duplicate records, coding issues, and inconsistent entries are identified and addressed, while variables are prepared for statistical testing.
Statistical methods are selected according to the research questions, study design, and characteristics of the data. The selected methods are then mapped to the specific analyses required for the study.
The required statistical analyses are performed in Stata using suitable commands and procedures. Stata do-files are used to document the analysis steps and maintain a clear record of the work performed.
The analysis is reviewed using relevant statistical diagnostics to identify problems that may affect the validity or reliability of the results. Where necessary, the model or analytical approach is adjusted.
The statistical output is examined to identify meaningful findings from the analysis. Results are interpreted in relation to the research questions, hypotheses, and variables rather than presenting Stata output without explanation.
The findings are presented through appropriate statistical tables, figures, and written explanations. Results are structured so they can be incorporated clearly into the relevant sections of the PhD thesis.
The completed analysis is checked for consistency between the dataset, statistical procedures, outputs, and reported findings. The final Stata files, outputs, tables, figures, and supporting documentation are then prepared for delivery.
From raw data to defensible findings, Ondezx keeps every Stata analysis aligned with the study objectives and doctoral research requirements.
Experienced PhD Data Analysts: We understand the statistical requirements of doctoral research and select methods based on your research questions, objectives, hypotheses, and data.
Accurate Stata Analysis: We use Stata to perform statistical analysis carefully, from data preparation and model selection to estimation, diagnostics, and interpretation.
Method Selection & Validation: We help determine whether the selected statistical method is appropriate and check the key assumptions before interpreting the results.
Clear Statistical Interpretation: We explain Stata outputs in a way that connects the statistical findings with your research objectives and hypotheses.
Reproducible Analysis: We create well-organized Stata do-files so that the analysis can be reviewed, repeated, and modified when required.
Complex Analysis Support: We assist with advanced models, challenging datasets, unexpected results, and statistical issues that may arise during doctoral research.
Results & Methodology Support: We help present statistical procedures, findings, tables, and interpretations clearly within your methodology and results chapters.
Publication-Ready Results: We focus on producing well-structured statistical results that can support thesis submission, research papers, and journal publication.
Looking to add a professional touch to your doctoral study using Stata? To talk about your research needs, request a free consultation or get a custom quote from our experts.
Not sure about the proper statistical technique for your data? Please request a free 15-minute consultation, and our experts will determine the best analytical method for your study.