Module 1: Introduction to Clinical Research and Study Designs

·       Principles of clinical research

·       Types of clinical studies: observational vs. interventional

·       Randomized controlled trials (RCTs): design, advantages, limitations

·       Observational studies: cohort, case-control, cross-sectional designs

·       Choosing the appropriate study design for clinical research questions

·       Practical session: Identifying the appropriate study design for different clinical research scenarios.

Module 2: Ethical Considerations and Regulatory Frameworks in Clinical Research

·       History of ethical principles in clinical research (Nuremberg Code, Helsinki Declaration)

·       Informed consent process and documentation in clinical trials

·       Institutional Review Boards (IRBs) and ethical approval

·       Regulatory guidelines for clinical trials (e.g., ICH-GCP)

·       Data safety and monitoring boards (DSMBs)

·       Practical session: Reviewing and discussing the ethical aspects of a clinical trial protocol.

Module 3: Principles of Clinical Trial Design

·       Formulating research questions and hypotheses in clinical trials

·       Randomization techniques and their implementation

·       Blinding (masking) in clinical trials: types and importance

·       Sample size calculation and power analysis

·       Selection of study populations and eligibility criteria

·       Practical session: Calculating the sample size for a clinical trial using Stata.

Module 4: Data Management in Clinical Research Using Stata

·       Setting up a clinical research database in Stata

·       Data entry, cleaning, and validation techniques

·       Handling different data types and formats in Stata

·       Creating and managing study variables

·       Data quality control and assurance

·       Practical session: Importing and managing clinical data in Stata.

Module 5: Descriptive Statistics and Graphical Methods for Clinical Data in Stata

·       Summarizing continuous variables (mean, median, standard deviation, IQR) in Stata

·       Summarizing categorical variables (frequencies, percentages) in Stata

·       Generating appropriate graphs for clinical data (histograms, box plots, scatter plots) in Stata

·       Visualizing relationships between variables

·       Assessing data distribution and normality

·       Practical session: Performing descriptive statistics and generating relevant graphs in Stata.

Module 6: Hypothesis Testing for Comparing Groups in Clinical Research Using Stata

·       Principles of hypothesis testing: null and alternative hypotheses, p-values

·       Comparing means of two groups: t-tests (independent and paired) in Stata

·       Comparing means of multiple groups: ANOVA in Stata

·       Comparing proportions: chi-square test and Fisher's exact test in Stata

·       Interpreting statistical significance in clinical research

·       Practical session: Conducting t-tests, ANOVA, and chi-square tests in Stata.

Module 7: Linear Regression Analysis for Clinical Data Using Stata

·       Examining linear relationships between continuous variables

·       Building and interpreting simple and multiple linear regression models in Stata

·       Assessing model fit and assumptions

·       Confounding and effect modification

·       Reporting regression results in clinical research

·       Practical session: Performing linear regression analysis in Stata to examine the relationship between clinical variables.

Module 8: Logistic Regression Analysis for Clinical Data Using Stata

·       Modeling binary outcomes (e.g., disease vs. no disease)

·       Building and interpreting logistic regression models in Stata

·       Odds ratios and their clinical interpretation

·       Assessing model fit and predictive ability

·       Confounding and interaction in logistic regression

·       Practical session: Performing logistic regression analysis in Stata to predict a binary clinical outcome.

Module 9: Survival Analysis for Time-to-Event Data Using Stata

·       Introduction to time-to-event data and censoring

·       Kaplan-Meier survival curves and log-rank test in Stata

·       Cox proportional hazards regression: building and interpreting models in Stata

·       Hazard ratios and their clinical interpretation

·       Assessing the proportional hazards assumption

·       Practical session: Conducting survival analysis using Stata to analyze time-to-event clinical data.

Module 10: Analysis of Correlated Data in Clinical Research Using Stata

·       Understanding correlated data (e.g., repeated measures, clustered data)

·       Linear mixed-effects models for longitudinal clinical data in Stata

·       Generalized estimating equations (GEE) for correlated outcomes in Stata

·       Choosing between mixed-effects models and GEE

·       Interpreting results from models for correlated data

·       Practical session: Analyzing longitudinal clinical data using linear mixed-effects models in Stata.

Module 11: Handling Missing Data in Clinical Research Using Stata

·       Types of missing data mechanisms (MCAR, MAR, MNAR)

·       Assessing patterns of missing data

·       Complete case analysis and its limitations

·       Imputation techniques for missing data in Stata (e.g., multiple imputation)

·       Sensitivity analysis for missing data

·       Practical session: Applying multiple imputation techniques to handle missing data in a clinical dataset using Stata.

Module 12: Interpreting Statistical Output and Drawing Conclusions in Clinical Research

·       Understanding the difference between statistical significance and clinical significance

·       Interpreting p-values, confidence intervals, and effect sizes in clinical research

·       Reporting statistical results clearly and accurately

·       Discussing the limitations of statistical analysis in clinical research

·       Translating statistical findings into clinical practice implications

• Practical session: Interpreting the output from various statistical analyses conducted in previous modules in the context of clinical research questions.

Module 13: Meta-Analysis: Principles and Application in Stata

·       Introduction to systematic reviews and meta-analysis

·       Formulating a research question for meta-analysis

·       Searching and selecting relevant studies

·       Assessing the quality of included studies

·       Performing meta-analysis using Stata (fixed-effects and random-effects models)

·       Interpreting forest plots and assessing heterogeneity

·       Practical session: Conducting a basic meta-analysis using Stata.

Module 14: Statistical Programming in Stata for Clinical Research: Introduction to Do-Files

·       Introduction to Stata do-files for reproducible research

·       Basic Stata programming commands and syntax

·       Automating data management and analysis tasks

·       Writing loops and conditional statements

·       Creating user-defined programs (macros)

·       Practical session: Writing a basic Stata do-file to automate a data analysis task.

Module 15: Advanced Regression Techniques in Clinical Research Using Stata

·       Poisson regression for count data

·       Negative binomial regression for overdispersed count data

·       Ordinal logistic regression for ordinal outcomes

·       Multinomial logistic regression for nominal outcomes

·       Model selection and validation techniques

·       Practical session: Applying Poisson regression to analyze count data in clinical research using Stata.

Module 16: Causal Inference in Clinical Research: Introduction to Potential Outcomes Framework

·       The concept of causality in observational studies

·       Potential outcomes framework

·       Confounding and methods to address confounding (matching, stratification)

·       Instrumental variables in clinical research

·       Introduction to causal mediation analysis

Requirements:

·       Participants should be reasonably proficient in English.

·       Applicants must live up to Armstrong Global Institute admission criteria.

Terms and Conditions

1. Discounts: Organizations sponsoring Four Participants will have the 5th attend Free

2. What is catered for by the Course Fees: Fees cater for all requirements for the training – Learning materials, Lunches, Teas, Snacks and Certification. All participants will additionally cater for their travel and accommodation expenses, visa application, insurance, and other personal expenses.

3. Certificate Awarded: Participants are awarded Certificates of Participation at the end of the training.

4. The program content shown here is for guidance purposes only. Our continuous course improvement process may lead to changes in topics and course structure.

5. Approval of Course: Our Programs are NITA Approved. Participating organizations can therefore claim reimbursement on fees paid in accordance with NITA Rules.

Booking for Training

Simply send an email to the Training Officer on training@armstrongglobalinstitute.com and we will send you a registration form. We advise you to book early to avoid missing a seat to this training.

Or call us on +254720272325 / +254725012095 / +254724452588

Payment Options

We provide 3 payment options, choose one for your convenience, and kindly make payments at least 5 days before the Training start date to reserve your seat:

1. Groups of 5 People and Above – Cheque Payments to: Armstrong Global Training & Development Center Limited should be paid in advance, 5 days to the training.

2. Invoice: We can send a bill directly to you or your company.

3. Deposit directly into Bank Account (Account details provided upon request)

Cancellation Policy

1. Payment for all courses includes a registration fee, which is non-refundable, and equals 15% of the total sum of the course fee.

2. Participants may cancel attendance 14 days or more prior to the training commencement date.

3. No refunds will be made 14 days or less before the training commencement date. However, participants who are unable to attend may opt to attend a similar training course at a later date or send a substitute participant provided the participation criteria have been met.

Tailor Made Courses

This training course can also be customized for your institution upon request for a minimum of 5 participants. You can have it conducted at our Training Centre or at a convenient location. For further inquiries, please contact us on Tel: +254720272325 / +254725012095 / +254724452588 or Email training@armstrongglobalinstitute.com

Accommodation and Airport Transfer

Accommodation and Airport Transfer is arranged upon request and at extra cost. For reservations contact the Training Officer on Email: training@armstrongglobalinstitute.com or on Tel: +254720272325 / +254725012095 / +254724452588