RESEARCH METHODS II JAMES KWAKU AGYEN

COURSE OUTLINE The course is designed to teach students to formulate - testable research hypotheses - utilize appropriate study designs - collect and analyze quantitative data - and interpret research findings - students will work on practical sessions to enhance the understanding of topics - to build skills in key techniques including literature review - Discussions and group activities will be organized to facilitate students’ interaction

COURSE OBJECTIVES By the end of this course students will be able to: - Demonstrate an understanding of the range of epidemiological study designs and their inherent threats to internal and external validity - Select the right designs for future research projects - Describe the basic issues related to measurement of variables - Identify problems with measurement reliability and validity - Select appropriate analytic techniques for each study design - Develop students’ skills in formal, scientific writing

COURSE CONTENT Project planning Literature review Variables and relationships Non-experimental including qualitative research designs, experimental research designs; sampling designs and procedures Assigning subjects to study groups Measurement concepts and methods Statistical analysis plan Reporting research findings

REFERENCES Recommended texts Aday LA and Cornelius LJ Designing and Conducting Health Surveys: A Comprehensive Guide (2006) 3 rd Ed Jossey-Bass, San Francisco Ader HJ and Mellenbergh GJ (eds.) Research Methodology in the Social, Behavioral & Life Sciences (1999) Sage Publications, Thousand Oaks, CA Aveyard H. Doing literature review in health and social care. A practical guide (2007). Open University Press, McGraw-Hill Education Green Judith and Thorogoo N (Eds) Qualitative Methods for Health Research (2004) Sage, London

OBJECTIVES At the end of this session you should be able to: 1. Describe data in terms of frequency distributions, percentages, and proportions. 2. Use figures to present data. 3. Explain the difference between mean, median and mode. 4. Calculate the frequencies, percentages, proportions, ratios, rates, means, medians, and modes for the major variables in your study that require such calculations. 5. Identify other independent variables, if any, that

INTRODUCTION Variable: a variable is a characteristic that takes on different values in different persons, places, or things. Some examples of variables include diastolic blood pressure, heart rate, the heights of adult males, the weights of preschool children, and the ages of patients seen in a dental clinic. In research, variables are chosen with the assumptions that they either; 1. would help us to define our problem (dependent variables) and its different components 2. or that they were contributory factors to the problem (independent variables) identified.

DNA & JKA RESEARCH METHODS II PROJECT PLANNING

OBJECTIVES The basic format of all research Research planning versus research methodology The nature and role of data in research Planning for data collection Identifying appropriate measurement instruments- Validity and Reliability Compare quantitative and qualitative approaches Ethical issues I research

Research Design Is a general strategy for solving a research problem Provides the overall structure for the procedures the researcher follows, the data the researcher collects, and the data analyses the researcher conducts Research Design – Research planning - this involves identifying your resources, your procedures, and the forms that your data will take - these are done with the central goal of solving your research problem in mind

THE BASIC FORMAT OF RESEARCH What we must note; Research process follows a basic format no matter which academic discipline gives rise to it That is, general procedure is fundamentally the same - Social science research, nursing research, etc In planning for a research design, one cannot be restricted by discipline-specific methodological restraints - e.g. a nurse may be wanting to solve a problem in her area and may encounter problems that are psychological - i.e. researchers must be willing to draw any productive

DO NOT DEPARTMENTALISE KNOWLEDGE Researchers do better by generating problems from broad generic areas within whose boundaries all research falls - Research problems may be generated from; people, things, records, thoughts and ideas, and dynamics and energy

Categories of Research Problems People: problems related to children, adults, families, communities, cultural groups, etc. Things: problems related to animal and vegetable life, viruses and bacteria, inanimate objects, matter, stars, galaxies, etc. Records: problems related to newspapers, journals, letters, minutes, legal documents, census reports, etc. Thoughts & Ideas: problems related to concepts, theories, perceptions, opinions, beliefs, etc. Dynamics & Energy: problems related to human interactions, metabolism, quantum mechanics, 4-13

1. A question is posed - In the mind of the researcher, a question arises that has no known resolution 2. it’s a matter of words - The researcher converts the question to a clearly stated research problem 3. it’s worth a guess - The researcher poses a temporary hypothesis or series of hypotheses 4. The search is on - The researcher searches the literature for ideas that shed light on the problem and for strategies that may THE BASIC FORMAT OF RESEARCH

5. Data - The researcher collects data that potentially relate to the problem 6. How do the data fit together? - The researcher arranges the data into a logical organizational structure. 7. The data speaks - The researcher analyzes and interprets the data to determine their meaning 8. Data supports or not -Either the data seemingly resolve the research problem or they do not. Either they support the hypotheses or they do not

Research Planning verses Research Methodology Research Planning: the general approach to planning a research study; is similar across disciplines -Data vary in nature. One cannot deal the same way with malaria in children as he/she will do with a historic document

Research Planning v. Research Methodology Therefore, in planning the research design -consider the kind of data the study will require -choosing viable research problem, reasonable way of collecting and interpreting the data Research Methodology -the techniques one uses to collect and analyze data; may be specific to a one’s discipline

Universality: -the research project should be one that might be carried out by any competent person. -The researcher is a catalyst who collects, organizes, and report what the collected data seem to indicate. General Criteria for a Research Project 4-17

Replication: -the research should be repeatable; -any other competent person should be able to take the problem and, collecting data under the same circumstances and within the same parameters you have used, achieve results comparable to yours. General Criteria for a Research Project

Control: -the researcher must isolate, or control, factors that are central to the research problem; control is important for replication and consistency within the research design. Measurement: the data should be able to be measured in some way General Criteria for a Research Project

The Nature and Role of Data in Research Data are transient and ever changing. Data are not absolute reality but manifestations of reality. Data is primary or secondary. - Primary data is the layer closest to the truth. - Secondary data are derived, not from the truth, but from primary data. Data must meet certain criteria to be admitted to study; any data not meeting the criteria are excluded from the study. Defective data may affect the validity of the research conclusions The restrictions used to admit certain data for

Planning for Data Collection Answers to the following questions will bring the process into focus What data are needed? Where are the data located? How will the data be obtained? How will the data be interpreted? 4-19

Identifying Appropriate Measurement Instruments We pin down data by measuring it in some way. Measurement instruments provide a basis on which the entire research effort rests. A research effort employing faulty measurement tools is of little value in solving the problem under investigation. In planning the research project, the nature of the measurement instruments should be clearly identified. Instrumentation should be described in explicit, concrete terms. Instruments should have 4-20 a reasonable degree of

Measurement is limiting the data: this means by a certain standard, we set limit to constrain the data; what is foot, a mile, a pound. They are each a unit of measure governed by a numerical constrain; so 12 inches constrains a foot, 5,280 Measurement as a Tool of Research Measurement: Is limiting the data of any phenomenon—substantial or insubstantial— so that those data may be interpreted and, ultimately, compared to a particular qualitative or quantitative standard. - Phrases in the definition;

“of any phenomenon-substantial or insubstantial”: this simply means that there is nothing a researcher cannot measure. - Substantial measurements those things being measured have physical substance, e.g. weight of a baby, diameter of a wire - Insubstantial measurements these exist only as concepts, ideas, opinions, feelings, or other intangible entities. e.g. the degree to which student have learned, the extent to Phrases in the definition

Four Scales of Measurement: Nominal Ordinal Interval Ratio Leedy & Ormrod Practical Research: Planning and Design, 10e © 2013 Pearson Education, Inc. All rights reserved. 4-23

Nominal Scale of Measurement Measures data by assigning names Things can be measured nominally in an infinite number of ways Simplistic Divides data into discrete categories Statistical procedures = mode, percentage, chi-square test Leedy & Ormrod Practical Research: Planning and Design, 10e © 2013 Pearson Education, Inc. All rights reserved. 4-24

Ordinal Scale of Measurement Think in terms of symbols (>; <) that is we can compare various pieces of data in terms of one being greater than the other This scale allows to rank-order data, thus the name ordinal. NB: Difference in ranks is meaningless - e.g. level of education can be measured on the ordinal scale by unschooled, elementary, high school, college or graduate education - Lecturers can be measured as assistant lecturer, lecturer, senior lecturer, associate professor, and professor Statistical procedures used; median, percentile

Interval Scale of Measurement This scale of measurement is characterized by two features: 1. Has equal units of measurement, as on the number line but 2x does not mean twice x on the scale 2. Zero point established arbitrarily (zero does not mean the total absence of the quality being measured) e.g. temperature measurement scales such as the Fahrenheit (F) and Celsius (C) Rating scales, such as those used in surveys, are interval scales. Statistical procedures = means, standard

Ratio Scale of Measurement Characterized by equal measurement units (similar to an interval scale) Has an absolute zero point (zero means total absence of the quality being measured) and ”minus” distance is not possible Can express values in terms of multiples and fractional parts, therefore, 2x means twice x. e.g. a yard is a multiple i.e. 36 times a 1-inch distance; an inch is one twelfth, a fraction part, of a foot Ratios are true ratios (Yardstick, feet) e.g. 36:1 and 1:12. it allows us to make comparisons that involve multiplication or division

Summary of the Scales of Measurement Nominal scale: One object is different from another. Ordinal scale: One object is bigger or better or more of anything than another. Interval scale: One object is so many units (degrees, inches) more than another, but zero does not mean total absence of the quality in measurement Ratio scale: One object is so many times as big or bright or tall or heavy as another, zero means total absence of the quality in measurement

Validity & Reliability of Measurement Validity = the extent to which a measurement instrument measures what it is intended to measure. Reliability = the consistency with which a measurement instrument yields a certain result when the entity being measured has not changed. Leedy & Ormrod Practical Research: Planning and Design, 10e © 2013 Pearson Education, Inc. All rights reserved. 4-30

Validity of Measurement Instruments Face Validity: the extent to which an instrument looks like it ’ s measuring a particular characteristic; relies on subjective judgment. Content Validity: the extent to which a measurement instrument is a representative sample of the content area being measured. E.g. If it reflects various parts of the content behaviors domain in appropriate proportions and requires central to that domain. Example assessing peoples achievement in some area Criterion Validity: the extent to which the results of an assessment correlate with another, related measure. E.g. salesperson’s effectiveness Construct Validity: the extent to which an instrument measures a characteristic that 4-31 cannot be directly observed

Ways to Demonstrate the Validity of a Measurement Instrument Table of specifications: the researcher constructs a two-dimensional grid listing the specific topics and behaviors that reflect achievement in the domain. Multitrait-multimethod approach: two or more different characteristics are each measured using two or more different approaches. The two measures of the same characteristic should be highly related. Judgment by a panel of experts: several experts in a particular area are asked to scrutinize an instrument to to ascertain its validity for measuring the characteristic in question. Leedy & Ormrod Practical Research: Planning and Design, 10e © 2013 Pearson Education, Inc. All rights reserved. 4-32

Reliability Reliability is the consistency with which a measuring instrument yields a certain result when the entity being measured hasn’t changed. Instruments designed to measure social and psychological characteristics (insubstantial phenomena) tend to be even less reliable than those designed to measure physical (substantial) phenomena. Leedy & Ormrod Practical Research: Planning and Design, 10e © 2013 Pearson Education, Inc. All rights reserved. 4-33

Determining the Reliability of a Measurement Instrument Interrater reliability: the extent to which two or more individuals evaluating the same product or performance give identical judgments. Internal consistency reliability: the extent to which all of the items within a single instrument yield similar results. Equivalent forms reliability: the extent to which two different versions of the same instrument yield similar results. Test-retest reliability: the extent to which a single instrument yields the same results for the same people on two different occasions. Leedy & Ormrod Practical Research: Planning and Design, 10e © 2013 Pearson Education, Inc. All rights reserved. 4-34

Quantitative vs. Qualitative Approaches Quantitative Research: involves looking at amounts, or quantities, of one or more variables of interest. Researchers attempt to measure variables in some way. Qualitative Research: involves looking at characteristics, or qualities, that cannot easily be reduced to numerical values. Researchers attempt to examine nuances and complexities of a particular phenomenon. Quantitative and Qualitative Processes ▪ formation of one or more hypotheses ▪ review of the related literature ▪ collection and analysis of data Leedy & Ormrod Practical Research: Planning and Design, 10e © 2013 Pearson Education, Inc. All rights reserved. 4-35

Quantitative vs Qualitative Research A Comparison Purpose quantitative -- seeks explanations and predictions that are generalizable. To establish, confirm, or validate relationships and to develop generalizations that contribute to existing theories qualitative -- seeks better understanding of complex situations. Process quantitative -- methods defined before study begins; allows objective measurement; researchers remain detached qualitative -- holistic/emergent; researchers remain open and immerse themselves in the complexity of the situation and interact with participants; variables emerge from data.

Quantitative vs. Qualitative Research A Comparison Data Collection quantitative -- data collected in form that is easily converted to numbers qualitative -- researcher is the research instrument; verbal and nonverbal data collected. They operate under the assumption that reality is not easily divided discrete measurable variables Reporting Findings quantitative -- data reduced to averages; scientific styles of reporting qualitative -- construct interpretive narratives from data

Combining Quantitative and Qualitative Designs Mixed-method design provides a more complete picture of a particular phenomenon than either approach could do alone

Qualitative or Quantitative? Guidelines Consider your own comfort with the assumptions of the qualitative tradition. Consider the audience for your study. Consider the nature of the research question. Consider the extensiveness of the related literature. Consider the depth of what you wish to discover. Consider the amount of time you have available for conducting the study. Consider the extent to which you are willing to interact with the people in your study. Consider the extent to which you feel comfortable working without much structure. Consider your ability to organize and draw inferences from a large body of information.

Considering the Validity of Your Method The validity of the research project as a whole means its accuracy, meaningfulness, and credibility. Researchers should consider two questions: 1. Does the study have sufficient controls to ensure that the conclusions drawn are truly warranted by the data? 2. Can the results obtained reasonably be used to make generalizations about the world beyond that specific research context? The answers to these two questions address the issues of internal validity and external validity, respectively.

Internal vs External Validity Internal Validity: the extent to which the design and data of a research study allow the researcher to draw accurate conclusions about cause-and-effect and other relationships within the data. External Validity: the extent to which the results of a research study apply to situations beyond the study itself; the extent to which conclusions can be generalized.

Strategies to Increase Internal Validity Conduct a controlled laboratory study Conduct a double-blind experiment Use unobtrusive measures Use triangulation

Strategies to Increase External Validity Conduct the study in a real-life setting. Use a representative sample. Replicate the study in a different context.

Validity in Qualitative Research Spend extensive time in the field. Spend extensive time in the field Conduct a negative case analysis. Contradict existing hypotheses, then continually revise them until all cases are accounted for Use thick description. Readers able to draw their own conclusion Seek feedback from others.

Ethical Issues in Research Assurances Honesty with professional colleagues Internal Review Board (IRB) Protection from harm Informed consent Right to privacy Professional code of ethics

The Value of a Pilot Study Pilot study: a brief exploratory investigation before the main study – to try out particular procedures, measurement instruments, or methods of analysis. – to determine the feasibility of the study. – to identify what approaches will and will not be effective in solving the overall research problem.

THANK YOU