Our statistical services support in representing, organizing and analyzing quantitative data obtained during evidence synthesis. We provide assistance in descriptive as well as inferential statistical analysis. Our team can handle various analytical procedures used in research such as:
- Exploratory analysis
- Sample size estimation based on study objective
- Statistical inputs for protocol and SAP development
- Statistical modeling
- Hypothesis testing, Estimation, Confidence intervals, Multiple comparisons
- Survival analysis
- Meta-analysis and visualization
- Network meta-analysis – Bayesian approach
- Detailed report on analyses and outputs as per the specifications
Evidence-based analytics toolkits:
We at Molecular connections strive to create a platform that can enable perspective-based decision making by the stakeholders. Our Statistical Evidence-based toolkits are designed to fill the gaps between traditional and time-consuming approaches of data analysis into a dynamic analytical framework combining our statistical and programming expertise.
Our statistical programmers create customized visuals using R libraries, interactive analytical interfaces for real-time visualization of data, and analysis specific to project requirements using R-Shiny platform.
We provide statistical platforms for representing, organizing as well as visualizing the quantitative data obtained from evidence synthesis. Our key statistical support systems include:
- Dynamic exploratory analysis/visualization: Helps to drill down into the data sets to be analyzed and develop interactive dynamic graphics. Our statistical apps provide real time insights and helps in comparative analysis and to identify gaps in the evidence.
- Interactive meta-analysis: Our customized evidence-based analytics toolkit provides evidence synthesis data from studies with comparative interventions as well combinations of interventions and a measurement of these interventions in a user-friendly, interactive manner.
- New study designs: Our clinical study design stat calculator provides sample size and power analysis for different study designs and outcomes based on the existing body of evidence. Our demonstrative app for sample size calculation, provides sample size calculation for a prospective RCT based on the results of meta-analysis of existing evidence.