Mixed Research Methods Qualitative Data Analysis Using NVivo and Quantitative Data Analysis of Panel Data Using Stata

4 months ago Posted By : User Ref No: WURUR173182 0
  • Image
  • TypeTraining or Development Class
  • Image
  • Location Kigali, Rwanda,Kigali,Rwanda
  • Price
  • Date 19-02-2024 - 01-03-2024
Training or Development Class Title
Mixed Research Methods Qualitative Data Analysis Using NVivo and Quantitative Data Analysis of Panel Data Using Stata
Event Type
Training or Development Class
Training or Development Class Date
19-02-2024 to 01-03-2024
Last Date for Applying
14-02-2024
Location
Kigali, Rwanda,Kigali,Rwanda
Organization Name / Organize By
FineResults Research Services Limited
Organizing/Related Departments
Research
Organization Type
Organization
Training or Development ClassCategory
Both (Technical & Non Technical)
Training or Development ClassLevel
All (State/Province/Region, National & International)
Related Industries

Research/Science

Social Sciences

Information Technology

Location
Kigali, Rwanda,Kigali,Rwanda

FineResults Research Services would like to invite you to take part in our upcoming workshops on  Research Courses at our FineResults Research Services training facilities in Nairobi, Kenya or online.

19/02/2024- 01/03/2023 Mixed Research Methods Qualitative Data Analysis Using NVivo and Quantitative Data Analysis of Panel Data Using Stata

 

 

INTRODUCTION

A mixed method research design allows researchers to collect and analyse both quantitative and qualitative data within the same study. With the approach overall goal of providing a better and deeper understanding, by providing a fuller picture that can enhance description and understanding of the phenomena, use of the right data collection tools and analyzing software are essential. This 10 days course will focus on designing tools for data collection that ensures real, quality, and rich data including capturing of videos, audios, and images. The course will also demonstrate both qualitative and quantitative research designs. While the course will explore quantitative data analysis using Stata 14, qualitative data will be analysed using Nvivo 14 software. Additionally, participants will be trained on interpretation of results and writing different research outputs among them project report, scientific journal articles, blogs, case studies and policy briefs.

 

DURATION

10 Days

 

COURSE OBJECTIVES

By the end of the course the learner should be able to:

  • Understand qualitative analysis approaches
  • Understand different qualitative data collection methods
  • Set up a project in NVivo
  • Create a framework for qualitative data analysis using NVivo
  • Carry out qualitative data analysis using NVivo
  • Write a qualitative report
  • Usefulness and problems with Panel Data
  • Opportunities and challenges of panel data.
  • Linear models data analysis with dynamic data
  • Logistic regression models with dynamic data
  • Count data models with dynamic data
  • Linear structural equation models with dynamic data

 

COURSE OUTLINE

Module 1: Introduction

Introduction to Qualitative Research

  • What is qualitative research?
  • Dimensions of qualitative methods
  • Qualitative research approaches
  • Qualitative data collection methods
  • Qualitative research study design

 

Preliminaries of Qualitative data Analysis

  • What is qualitative data analysis
  • Approaches in Qualitative data analysis; deductive and inductive approach
  • Points of focus in analysis of text data
  • Principles of Qualitative data analysis
  • Process of Qualitative data analysis

 

Introduction to NVivo

  • NVivo Key terms
  • NVivo interface
  • NVivo workspace
  • Use of NVivo ribbons

 

Module 2: Project Management

NVivo Projects

  • Creating new projects
  • Merging, importing and exporting projects
  • Managing projects
  • Working with different data sources

 

Nodes in NVivo

  • Theme codes
  • Case nodes
  • Relationships nodes
  • Node matrices

 

Classifications

  • Source classifications
  • Case classifications
  • Node classifications

 

Module 3: Coding and Analysis

Coding

  • Data-driven vs theory-driven coding
  • Analytic coding
  • Descriptive coding
  • Thematic coding
  • Tree coding

 

Thematic Analysis using NVivo

  • Organize, store and retrieve data
  • Cluster sources based on the words they contain
  • Text searches and word counts through word frequency queries.
  • Examine themes and structure in your content

 

Memos Annotations and Links

  • Linked memos
  • Adding annotation to selected content
  • See also link

 

Queries using NVivo

  • Queries for textual analysis
  • Queries for exploring coding

 

Module 4: Analysis, interpretation and visualization

Building on the Analysis

  • Content Analysis; Descriptive, interpretative
  • Narrative Analysis
  • Discourse Analysis
  • Grounded Theory

 

Qualitative Analysis Results Interpretation

  • Comparing analysis results with research questions
  • Summarizing finding under major categories
  • Drawing conclusions and lessons learned

 

Visualizing NVivo project

  • Display data in charts
  • Creating models and graphs to visualize connections
  • Tree maps and cluster analysis diagrams

 

Module 5: Triangulation of Data Sources and Reporting

Triangulation of Data Sources

  • Triangulating with quantitative data
  • Using different participatory techniques to measure the same indicator
  • Comparing analysis from different data sources
  • Checking the consistency on respondent on similar topic

 

Qualitative Report Writing

  • Qualitative report format
  • Reporting qualitative research
  • Reporting content
  • Interpretation

 

QUANTITATIVE DATA ANALYSIS OF PANEL DATA USING STATA

Module 6: Introduction

Introduction to Panel Data

  • Why Are Panel Data Desirable?
  • Problems with Panel Data
  • Examples of Time-varying and time-invariant variables

 

Opportunities and challenges of panel data

  • Data requirements
  • Control for unobservables
  • Determining causal order
  • Problem of dependence
  • Software considerations

 

Module 7: Linear models

  • Robust standard errors
  • Generalized estimating equations
  • Random effects models
  • Fixed effects models
  • Between-within models

 

Module 8: Logistic regression models

  • Robust standard errors
  • GEE
  • Subject-specific vs. population averaged methods
  • Random effects models
  • Fixed effects models
  • Between-within models

 

Module 9: Count data models

  • Poisson models
  • Negative binomial models

 

Module 10: Linear structural equation models

  • Fixed and random effects in the SEM context
  • Models for reciprocal causation with lagged effects

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TRAINING CUSTOMIZATION

This training can also be customized for your institution upon request. You can also have it delivered your preferred location. For further inquiries, please contact us through Mobile: +254 732 776 700 or +254 759 285 295. You can also send an email: [email protected]

 

REQUIREMENTS

Participants should be reasonably proficient in English. During the trainings, participants should come with their own laptops.

 

TRAINING FEE

The course fee covers the course tuition, training materials, two break refreshments, lunch, and study visits.

 

ACCOMMODATION

Accommodation is arranged upon request. For reservations contact us through Mobile: +254 732 776 700 or +254 759 285 295. You can also send an email: [email protected]

PAYMENT

Payment should be transferred to FineResults Research Limited bank before commencement of training. Send proof of payment through the email: [email protected]

 

CANCELLATION POLICY

  • All requests for cancellations must be received in writing.
  • Changes will become effective on the date of written confirmation being received.

 

 

Registration Fees
Available
Registration Fees Details
USD 1800
Registration Ways
Email
Phone
Website
Address/Venue
Kigali, Rwanda  FineResults Research Training Centre 
Contact
Edith Wairimu

[email protected]

   +254 759 285 295
Samuel Wamuyu

[email protected]

   +254 732 776 700