With the dawn of the 21st century, those who work for population and health face the daunting challenge of improving population health. Meeting this challenge will require evidence-based practice to guide policies and programs. Quantitative research provides information to build evidence. Collecting, analyzing and synthesizing quantitative data makes information relevant to decision making. Quantitative research has developed tremendously over the years and constitutes the cornerstone of health preservation for the healthy and restoration of health to the unhealthy. This module aims to provide participants with an in-depth understanding of quantitative research. Participants will combine the concepts and methods of epidemiology, statistics and demography in an approach that integrates these into social research. This module will place a special emphasis on development and equity measurements.

The main aims of this module include:

• Provide fundamental knowledge and understanding of quantitative research

• Enhance participants capabilities to collect, process, describe, analyze, interpret and disseminate quantitative data

• Introduce participants to the various data sources and the available data sets for Arab countries

• Develop participants skills in the use of development and equity measures

At the end of Module II participants are expected to understand:

• The basis of quantitative research
• The quantitative research design process
• Data collection techniques
• Data processing
• Describing and analyzing data
• Interpretation and dissemination of results

Participants are expected to be capable of:

• Designing data collection tools
• Data description
• Data analyses
• Interpretation and dissemination of results
• Practicing secondary analysis
• Developing scientific articles
• Presentation of scientific articles

Participants are expected to develop computer skills using:

• Microsoft Access

• SPSS

• STATA

The module is designed to provide an in-depth understanding of the concepts and methods of epidemiology, statistics and demography in an integrative approach that brings together these disciplines in social research. The stress in this module is on the logic of what is done in quantitative research, as well as its technical aspects. Therefore, it provides both understanding and practice of the quantitative research approach. The course introduces trainees to the principles of research and the methods used in the quantitative approach. It also provides participants with the knowledge needed to determine appropriate epidemiologic and statistical methods. The course allows trainees to develop their interpersonal and group communication skills; it also provides them with the basic skills required to utilize commonly used statistical computer packages. Trainees will develop these skills through the practice of secondary analysis, reporting of results in the form of a scientific article and professional presentation. The module covers the following topics:

This section of module II aids trainees in the development of their understanding of the various sources of data, as well as the availability of data sets for the Arab countries. Participants will be introduced to the various sources of data for research. They will also be introduced to the international data sets. Finally, participants will explore the population and health data sets available for Arab countries.

In this section trainees will be taught the potential research errors (random and systematic errors); as well as how to prevent them at the research planning stage and control them during the data analysis and interpretation of results. Trainees will also be introduced to the various epidemiologic study designs, as well as their strengths and limitations.

Trainees will develop an understanding of the methods needed to choose a target population, as well as selecting the study population. Finally, participants will be introduced to population-based and sample-based research. Lectures will cover a range of topics including sampling techniques (probability and non-probability sampling), sampling hidden and heard-to-reach populations, sampling frames, sample size calculation and sampling error.

This section introduces the methods of data processing, as well as quality control techniques. Participants will be introduced to the types of variables, data collection techniques and data management techniques (data management system, database concept, data entry, quality control). The weighing of data prior to analysis, the data transformation process (data reduction, creation of composite variables) and data presentation methods will also be demonstrated. Participants will apply concepts in group work and computer applications.

This section covers summary statistics, indices of population and health, as well as statistical inference. Participants will be expected to become familiar with the following summary statistics:

• Descriptive statistics (measures of central tendency and dispersion)

• Tools for summarizing qualitative data (count, ratio, proportion, rate)

• Measures of health (cumulative incidence, incidence density, attack rate, secondary attack rate, point prevalence, and period prevalence)

• Measures of population composition (age-child ratio, population momentum, masculinity proportion, sex ratio excess/deficit male proportion)

• Measures of years of life lost and years of life lived with disability

• Measures of association (relative risk, odds ratio, attributable risk, population attributable risk)

• Measures of equity for 2 groups (rate ratio, rate difference, low-to-high ratio, shortfall

• Measures of equity for more than 2 groups (slope index, concentration index, index of dissimilarity)

• Measures of correlation (pearson’s spearman’s, kendall tau, phi, cramér, kappa)

• Inter-individual measures of equity (Gini coefficient and Lorenzo curve)

Participants will be expected to become familiar with the following indices of population and health:

• General indices (crude rate, specific rate, direct standard rate, indirect standard rate, cause-specific mortality rate, case-fatality rate, proportional mortality, proportional mortality ratio

• Indices of maternal and child health (maternal mortality ratio, maternal mortality rate, fetal death rate, perinatal mortality rate, neonatal mortality rate, infant mortality rate, child mortality rate, under-five mortality rate)

• Indices of fertility (crude birth rate, general fertility rate, age-specific fertility rate, total fertility rate, gross reproduction rate, net reproduction rate, )

• Indices of human development (human development index, human poverty index, gender-related development index, gender empowerment index)

Finally, participants will be educated on the requirements for a statistical inference; these include a research hypothesis, type I error, Type II error, probability level for a, and finally, evaluating the role of chance. Relevant statistical inferences are listed below:

• Confidence interval (for means, proportions, relative risk and odds ratio)

• Tests of statistical significance for question problem of estimation (for a single mean, for a single proportion)

• Tests of statistical significance for question problem of comparison (between 2 or more means, two or more proportions for independent and paired samples, for trend in proportions)

• Tests of statistical significance for question problem of correlation (for different correlation coefficients)

• Regression (simple linear, multiple linear, logistic)

• Decomposition of concentration index

This section elucidates the various approaches needed for result communication; and demonstrates that these approaches are dependent on the target audience. The main objectives for a successful communication include reliability, validity, causation and association, and the judgment of a cause-effect association. Participants are expected to communicate the results of their scientific article in a professional presentation.

Participants will apply the knowledge above in order to write a scientific article after a secondary analysis on a population and/or health topic with an equity lens based on the DHS-Egypt 2005 data set. Participants will also benefit from the required computer application sessions.

1. Written material that includes

• Written exercises
• Assignments
• Scientific article

2. Formal oral professional presentations of the scientific paper

3. Computer application exercises