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      Epidemiology and Bio-statistics using Stata Training Course in Nairobi


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      August 10, 2020

      Monday   8:00 AM - 5:30 PM

      westlands nairobi
      Nairobi, Nairobi Municipality

      Performers:
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      EVENT DETAILS
      Epidemiology and Bio-statistics using Stata Training Course

      FineResults Research Services invites you to training on:
      Topics: Epidemiology and Bio-statistics using Stata
      Date: 10th to 21st August 2020
      Cost: USD 1600 or Ksh 120,000
      Contacts: +254 759 285 295, training@fineresultsresearch.org.
      Venue : FineResults Research, Nairobi, Kenya Training Centre.
      INTRODUCTION
      Participants will learn the principles of epidemiology and biostatistics and gain skills in using epidemiological and biostatistician tools to describe monitor and investigate the determinants of population health. The statistical background required to conduct research, describe, summarize, develop hypothesis, assess associations, analyze data, interpret and communicate results will be studied comprehensively. The course targets health care professionals who wish to consolidate their knowledge and skills and increase their understanding of the importance of epidemiology and statistics in public health today.

      DURATION
      10 Days

      COURSE OBJECTIVES
      At the end of the course, participants will be able to:
      • Use epidemiological and biostatistician tools to describe, monitor and investigate the determinants of population health.
      • Gain key statistical background necessary for conducting valid research
      • Describe and summarize data
      • Develop hypothesis and analyze data.
      • Interpret and communicate results

      Module 1:
      1. Data management & graphics in Stata
      Introduction to Stata
      • Starting Stata
      • Setting layout
      • Directory management commands
      • Data types in Stata
      • Using Stata as a calculator
      • Stata command and options
      • Stata do-files
      • Creating data sets directly in Stata
      • Rename of variables
      • Managing variables and/or variable properties
      • Importing data from other software
      • Exporting data to other software
      • Loading data into the memory
      • The in and if qualifiers
      • The by prefix
      • Create subsets (keep and drop)
      • Create random variables (from distributions)
      • Random sampling
      • Sort variables
      • Change order of variables
      • Count number of observations
      • Generate sequential numbers
      • Working with dates
      • Viewing data sets
      • Interrupting computations
      • Help

      Module 2:
      Creating and changing variables
      • Create new variables
      • Extended generate command
      • Duplicate an existing variable
      • Replace contents of a variable
      • Convert numeric to string
      • Convert string numbers to numeric
      • Convert numeric values to missing and vice versa
      • Recode string variables
      • Decode numerically coded variables
      • Transforming a continuous variable to categorical
      • Reduce number of categories of a categorical variable
      • Managing duplicates

      Transforming variables and data sets
      • Split variables
      • Extract parts of variables
      • Standardize variables
      • Create dummy variables
      • Create separate variables
      • Transpose variables
      • Stack variables
      • Unstack variables
      • Appending data sets
      • Combining data sets by a common variable
      • Convert datasets from wide to long
      • Convert datasets from long to wide
      • Some application to data cleaning

      Introduction to Stata graphics
      • The graphics dialog windows
      • Graph elements (x and y labels, titles, legends)
      • Graph appearance (marker symbol, color, size, line
      • width, pattern, e.t.c)
      • Multiple graphs (by option)
      • Graphics syntax
      • Adding text and annotations to graphs
      • Saving and printing graphs
      • Combining active graphs into one figure
      • Graphics window (interactive plotting)
      • Common graphs and charts

      Module 3:
      2. Biostatistics
      Introduction to statistical concepts
      • Review of research process
      • Research designs
      • Sampling techniques
      • Types of data
      • Descriptive statistics
      • Graphs for descriptive statistics
      Hypothesis testing
      • Definitions
      • Statistical inference
      • Generalizability
      • Confidence intervals in clinical research
      • P-values in clinical research
      • Hypothesis testing
      • Interpreting hypothesis test results

      Tests of differences in population means
      • One sample t tests
      • Two sample independent t tests
      • Two sample paired t test
      • One way analysis of variance
      • Two way analysis of variance

      Module 4:
      Analysis of contingency tables
      • Introduction
      • Two by two tables: Proportion test
      • Two by two tables: Fisher’s exact test
      • McNemar matched pairs for binary response
      • Other measures of association

      Non-parametric methods
      • Sign test
      • Wilcoxon signed-rank test
      • Median test
      • Wilcoxon signed-sum (Mann-Whitney) test
      • Kolmogorov-Sminorv goodness-of-fit test
      • Kruskal-Wallis one way analysis of variance
      • Friedman two-way analysis of variance
      • Spearman rank correlation
      • Nonparametric regression analysis

      Linear regression and correlation
      • Overview
      • Pearson correlation analysis
      • Simple linear regression
      • Multiple linear regression
      • Interpret results from linear regression
      • Regression diagnostics

      Module 5:
      3. Epidemiology
      Measures of disease frequency
      • Importance of measures of disease frequency
      • Measures of risk and association
      • Risk verses prevention
      • Prevalence
      • Incidence, cumulative incidence & incidence density
      • Relationship between prevalence and incidence
      • Stratification of disease frequency

      Module 6:
      Measures of effect for categorical data
      • Risk difference
      • Risk ratio
      • Attribute fraction
      • Attribute risk
      • Relative risk
      • Odds ratio

      Measures of effect for stratified categorical data
      • Mantel-Haenzsel test
      • Odds ratio for stratified data
      • Odds ratio for matched pairs studies
      • Testing for trends

      Vital statistics
      • Introduction
      • Death rates and ratios
      • Measures of fertility
      • Measures of morbidity

      Clinical research designs
      • Study population
      • Exposure and outcome
      • Study designs
      • Causation

      Module 7:
      Case report and series
      Cross-sectional studies
      Cohort studies
      • Cohort study design
      • Ascertainment
      • Advantages
      • Disadvantages
      • Poisson regression for cohort studies

      Case-control studies
      • Case-control study design
      • Advantages
      • Disadvantages
      • Unconditional logistic regression
      • Conditional logistic regression

      Misclassification
      • Definition
      • Non-differential misclassification
      • Differential misclassification
      • Assessing misclassification

      Module 8:
      Confounding
      • Confounding overview
      • Evaluation of confounding factors
      • Confounding by indication

      Remedies for confounding
      • Restriction
      • Stratification
      • Matching
      • Regression
      • Randomization
      • Interpretation after adjusting for confounding
      • Unadjusted verse adjusted association: confounding

      Effect modification
      • Overview
      • Synergy between exposure variables
      • Effect modification verses confounding
      • Evaluation of effect modification
      • Effect modification in clinical research articles
      • Effect modification on the relative and absolute scales

      Module 9:
      Introduction to survival analysis
      • Overview
      • Organizing survival data for computer use
      • Censoring (right and left)
      • Truncation (right and left)
      • Plotting survival data (the Kaplan-Meier curve)
      • Log-rank tests
      • Hazard rates
      • Cox proportional hazard models

      Module 10:
      Research ethics and statistics
      • Introduction
      • Protection of human research subjects
      • Informed consent
      • Equipoise
      • Research integrity
      • Authorship policies
      • Data and safety monitoring boards
      NB: We are offering you a half day, fun and interactive team building event!
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      Cost: Payment required - usd 1600

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