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Utilize EHRs, registries, and time-sensitive datasets to facilitate expedited, data-driven decision-making amidst health crises or policy assessment.
Full-Service Epidemiology Support for Research & Public Health
Examine disease distribution by person, place, and time to identify health patterns, generate hypotheses, and contribute to surveillance and outbreak monitoring.
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(Prospective/Retrospective) Identify risk factors by comparing outcomes in exposed and unexposed groups, all while keeping track of time—best for chronic disease and clinical outcome studies.
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Compare exposed and unexposed groups to discover elationships, when comparing those affected (the case) with those that are not (control)—widely used in the study of rare diseases.
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Assess the prevalence of disease and to assess exposure-outcome relationships at one given point in time—commonly used in popluation surveys and behavioral health studies.
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Use the statistical rigor of randomized trials to assess the effect of an intervention—registered as the gold standard in evaluating clinical trials and public health program effectiveness to evaluate the influence of specific policies.
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Benchmarking regression models to account for nested data structures and to control for a multitude of confounders—is common within policy, education, and healthcare studies.
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Analyze longitudinal health data to find seasonal patterns and assess an outbreak, assess the effect of a policy over time.
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Epidemiology Map health outcomes as physically situated, to help highlight disease clusters, environmental hazards or health inequities, such as in rural populations or other areas of refugee service.
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Reviews Summarize findings across multiple studies to provide the highest level of evidence – provides good evidence to support guideline development, HTA and policy recommendations.
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Simulating randomization in observational studies to help reduce confounding and assess treatment effect.
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Leveraging models such as DAGs and SEM to evaluate indicators of causality and to recognize mediators in the social and clinical pathway.
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Analyzing correlated/clustered longitudinal data
probability weighting Confounding control in observational studies.
Agruidng multi-study data for systematic review or evidence synthesis.
Probabilities under uncertainty estimation, small sample studies
Evaluating policy/intervention impacts over time
clusters of disease and geospatial patterns.  Â
We work with you to clarify the research question, develop a study design (e.g., cohort, case-control), and a suitable analysis in terms of your objectives.
We clean, harmonize, and standardize the data - whether from one or many sources; electronic health records (EHRs or similar), questionnaires, registry, etc. We resolve issues where there are discrepancies, and prepare variables for analysis.
Using a range of statistical tools and statistical techniques, we undertake statistical analyses with customized models relative to your study type (ensuring an analysis with accuracy, validity, and transparency).
Every analysis we conduct is subject to multiple reviews, including reproducibility, and checking assumptions, and approval from a subject mater expert (SME).
We translate statistics into useful findings, and contextualize information - with confidence intervals, visual aids, and plain language supporting summaries and notes for your stakeholders.
Intended reports, statistical models used, and data (in many different formats) will be paredd down according to your format of choice, available for publish, to submit, to use or share through your organization's registry or databases.
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We hired Statswork to conduct a meta-analysis of COVID-19 vaccine trials globally. Their work, which consisted of managing too large datasets, dealing with heterogeneity, and presenting clearly articulated pooled estimates, was fantastic. The statistical expertise and transparency in their report made our publication significantly better.
Statswork produced robust Cox models for our cancer survival analysis in the clinical oncology program. They precisely handled censoring and did multivariable stratification, as well as translating and converting the statistical output into barriers that could be understood by our Clinical Board. Their work was used to help guide data driven decisions on treatment planning.
We partnered with Statswork to investigate regional variations in dengue transmission. Their spatial regression, mapping, and hotspot analysis allowed us to get a much clearer picture of the areas associated with a high-risk transmission and facilitated interventions. We consider them a fully trusted data partner.
AI & ML
Predective Analyses
Data Analyses
Yes, we may support cohort studies, case-control studies, cross-sectional studies and ecological studies – always adapting our approach to the research project goals and data type.
Definitely. We deal with hospital records, national survey datasets, electronic health records (EHRs), insurance claims and any databases freely available publicly, for example the National Health and Nutrition Examination Survey, Demographic and Health Survey, etc.
We work with R, STATA, SAS, Python, Epi Info, and Bayesian tools such as JAGS and WinBUGS; ensuring that we align our methods with the best research methods used globally.
Every project has two levels of code checks and data validation, we conduct diagnostics of all models, and check model assumptions. We document everything to allow reproducibility of our results.
Yes. We can do data cleaning, imputation of missing data, deal with outliers and potentially transform your datasets to be in a state of readiness for analysis.
Yes, we use difference-in-differences, ITS and multilevel data, thoughtful analyses to assess public health interventions and impacts policy outcomes.
Absolutely. We frequently co-author peer-reviewed journal articles, white papers, or conference presentations with our clients.
We are compliant with GDPR, HIPAA, and other local ethical protocols. We sign NDAs, anonymize datasets, and work within secure digital spaces.
Yes. We provide retained services for research programs, grant-funded projects, or institutional epidemiology units.
Just send us information about your study objectives, relevant data, and research questions. We will swing a customized proposal your way with timelines, methodology, and pricing.
Statswork delivers comprehensive epidemiological support shored up to your study objectives. Work with our professionals experts for reliable, actionable, and publishable outcomes. So why wait? Reach out to us now!
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