Biostatistics

Biostatistics

Statistics is a commonly used term that includes both descriptive and analytical domains. Biostatistics data analysis is not just a part of statistics as it sounds, instead, it has its field. This method is generally used in the design and analysis of medical and public health research studies. It is central to all of science, as all the evidence and the evaluation for judgement is done through this method of statistics. While doing biostatistics in clinical research, disease or disorder incidence, and meta-analytic data, it is important to conduct appropriate statistical tests with predictive techniques. We at SPSS tutor, translate your research into lay terms to progress the research process. Our statistics help the company not only advance in quantitative methods, but also the life sciences, public health, and epidemiology. We hire advanced degree methodologies from every field of science, engineering, and social science fields to work on your behalf. Along with performing the biostatistics research, we also suggest to you the peculiarities that may be required in your research or if any additional analyses or diagnostics are required before the case description gets published.

At whichever level you are, we match you with the right team of academic researchers and methodologies to perform a rigorous analysis. This statistical consulting support gets started from the early stage of development itself and the services included in it are:-

    1. Grant research, writing, and editing (including literature search)
    2. IRB submission
    3. Protocol review
    4. Methodology review and design
    5. Statistical sampling and validation
    6. Questionnaire/interview protocol development and expert review
    7. Feasibility analysis
    8. Pivotal study design for 510(k) applications

After this early-stage research, we also provide you assistance in the following area:-

    1. Kaplan-Meier Survival Analysis
    2. Cox Regression
    3. Structural Equation Modeling (as implemented in MPLUS, AMOS and LISREL)
    4. Multilevel linear and Nonlinear Models
    5. Bayesian Analysis based on Markov Chain Monte Carlo methods
    6. Meta-analysis
    7. Knowledge graphing is done for “big” dataset development like public health, epidemiology
    8. For large scale, high dimensional public health and epidemiological datasets, machine learning estimation technique is utilised
    9. Open-ended questionnaires, group discussions, or interviews for follow-up qualitative research
    10. As per the journal reviewer’s feedback, Manuscript editing is done
    11. Third-party validation

We consult for groups of clinicians and individual investigators at the top research clinics also. These studies include the development of large datasets across numerous medical journals and epidemiological inquiries.

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