BIOSTATISTICS

1. BIOSTATISTICS Mahmoud Al Hussami,PhD., DSc. Associate Professor of Epidemiology

2. Unit One INTRODUCTION

3. It can be defined as the application of the mathematical tools used in statistics to the fields of biological sciences and medicine.  • It is a growing field with applications in many areas of biology including epidemiology, medical sciences, health sciences, educational research and environmental sciences. Biostatistics

4. Biostatistics is concerned withcollection, organization, summarization, and analysis of data. • We seek to draw inferences about a body of data when only a part of the data is observed. Concerns of Biostatistics

5. To describe and summarize information thereby reducing it to smaller, more meaningful sets of data. • To make predictions or to generalize about occurrences based on observations. • To identify associations, relationships or differences between the sets of observations. Purposes of Statistics

6. Data are numbers which can be measurements or can be obtained by counting.  • Biostatistics is concerned with the interpretation of the data and the communication of information about the data.    Data

7. Data are obtained from • Analysis of records • Surveys • Counting • Experiments • Reports Sources of data

8. Source of knowledge • Traditions. It involves the handing down of knowledge from one generation to another. • Authority. Experts. • Clinical Experience, Trial and Error, and Intuition. • Logical reasoning (inductive vs. deductive) • Disciplined research (borrowed research).

9. There are many ways to obtain information, including sensory experience, agreement with others, expert opinion, logic, and the scientific method. • The scientific method is considered by researchers the most likely way to produce reliable and accurate knowledge. Ways of Knowing

10. The scientific method involves answering questions through systematic data collation and analysis. • The scientific research uses empirical data (data gathered through the senses) and is a systematic orderly and objective method of seeking information. Ways of Knowing (continue)…

11. Is a method of knowing combines experience, intellectual faculties, and formal systems of thought. • Inductive Reasoning. Is the process of developing generations from specific observations. E.g., a nurse may observe the anxious behavior of (specific) hospitalized children and conclude that (in general) children's separation from their parents is stressful. • Deductive Reasoning. Is the process of developing specific perditions from general principles. Logical Reasoning

12. Inductive : from particular to generalization • Deductive : from general to specific, the conclusion are valid not true NO ONE ALONE IS ENOUGH, BOTH ARE A COMPLEMENTARY PARTS. Inductive vs. Deductive

13. Deductive Reasoning – A type of logic in which one goes from a general statement to a specific instance. • The classic example All men are mortal. (major premise) Socrates is a man. (minor premise) Therefore, Socrates is mortal. (conclusion) Deductive Reasoning

14. Inductive Reasoning, involves going from a series of specific cases to a general statement. The conclusion in an inductive argument is never guaranteed. Example: What is the next number in the sequence 6, 13, 20, 27,… There is more than one correct answer. Inductive Reasoning

15. The word “science” means knowledge. • The word “philosophy” means wisdom. • All research is based on philosophical beliefs about the world – world view or paradigm. • The perceived view is the basis of naturalistic (qualitative) research; the received view is the basis of empirical analytical (quantitative) research. PHILOSOPHIES OF RESEARCH

16. Paradigm: Is a world view; a general perspective on the complexities of the real world, with certain assumptions about reality. Paradigms for human inquiry are characterized in terms of the ways in which they respond to basic philosophical questions? • Ontology: the nature of reality • Epistemology: The relationship between inquirer and that being studied • Axiology: role of values in the inquiry • Methodology: how to obtain knowledge Paradigms for Health Research

17. Positivism (also modernism, logical positivism) • There is a reality out there that can be studies and known • Phenomenon is not haphazard or random • Highly objective in pursuit of knowledge • Rooted in 19th century thought. • Guided by such philosophers as Mill, Newton, & Locke. Naturalism (also phenomenologic, constructive) • Putting structures and ideas in a new ways • Reality is not fixed • Subjectivity is the primary way of understanding the phenomenon of interest. • Began as a countermovement to positivism with writers such as Weber & Kant. Major Paradigms

18. Positivist Paradigm Reality exists; there is a real world driven by real natural causes. Naturalistic Paradigm Reality is multiple and subjective, mentally constructed by individuals. Assumption: Ontologic “what is the nature of reality”?

19. Positivist Paradigm The inquirer is independent from those being researched; findings are not influenced by the researcher. Naturalistic Paradigm The inquirer interacts with those being researched; findings are the creation of the interactive process. Assumption: Epistemologic “How is the inquirer related to those being researched”?

20. Positivist Paradigm Values and biases are to be held in check; objectivity is sought. Naturalistic Paradigm Subjectivity and values are inevitable and desirable. Assumption: Axiologic “What is the role of values in the inquiry”?

21. Positivist Paradigm Deductive processes Emphasis on discrete, specific concepts. Verification of researchers’ hunches. Fixed design. Tight controls over contexts. Emphasis on measured, quantitative information; statistical analysis. Seeks generalizations. Naturalistic Paradigm Inductive processes. Emphasis on entirely of some phenomenon, holistic. Emerging interpretations grounded in participants’ experiences. Flexible design. Context-bound. Emphasis on narrative information; qualitative analysis. Seeks patterns. Assumption: Methodologic “How is knowledge obtained”?

22. Research methods are the techniques used by researchers to structure a study and to gather and analyze information relevant to the research question. • Quantitative research, which is most closely allied with the positivist tradition. • Qualitative research, which is most often associated with naturalistic inquiry. Methods of Research

23. Associated with positivism. • Use a scientific approach. • Mainly to understand the phenomenon of interest. • Use deductive reasoning to generate hunches that are tested in the real world. • Use mechanisms designed to control the study. • Researchers gather empirical evidence. • Must focus on human beings, who are inherently complex and diverse. Quantitative Research

24. Mainly to understand the human experience. • Rich and in-depth information. • Flexible. • Associated with naturalistic paradigm. • Use Inductive reasoning. Qualitative Research

25. A variable is an object, characteristic, or property that can have different values. • A quantitative variable can be measured in some way. • A qualitative variable is characterized by its inability to be measured but it can be sorted into categories. Variables

26. A random variable is one that cannot be predicted in advance because it arises by chance.  Observations or measurements are used to obtain the value of a random variable. • Random variables may be discrete or continuous. Random Variables

27. A discrete random variable has gaps or interruptions in the values that it can have. • The values may be whole numbers or have spaces between them. Discrete Random Variable

28. A continuous random variable does not have gaps in the values it can assume. • Its properties are like the real numbers. Continuous Random Variable

29. A population is the collection or set of all of the values that a variable may have.The entire category under consideration. • A sample is a part of a population.The portion of the population that is available, or to be made available, for analysis. Populations and Samples

30. Sampling: the process of selecting portion of the population. • Representativeness: the key characteristic of the sample is close to the population. • Sampling bias: excluding any subject without any scientific rational. Or not based on the major inclusion and exclusion criteria. Population and Sampling

31. Studying the self esteem and academic achievement among college students. • Population: all student who are enrolled in any college level. • Sample: students’ college at the University of Jordan. Example

32. Sampling is the selection of a number of study units/subjects from a defined population. What is sampling?

33. Reference population – to whom are the results going to be applied? • What is the group of people from which we want to draw a sample (study population)? • How many people do we need in our sample (Sample Size)? • How will these people be selected(Sampling Method)? Questions to Consider

34. Reference Population Sampling - Populations Study Population Sampling Frame Study Subjects

35. Is a complete set of persons or objects that possess some common characteristic that is of interest to the researcher. • Two groups: The target population The accessible population Population

36. The entire group of people or objects to which the researcher wishes to generalize the findings of a study. • Target population should meet the criteria of interest to the researcher • Example: all people who were admitted to the renal unit for dialysis in Al-Basheer hospital during the period of 2014 – 2016. Target Population

37. The group of people or objects that is available to the researcher for a particular study Accessible Population

38. STUDY POPULATION SAMPLING SAMPLE TARGET POPULATION

39. Element: The single member of the population (population element or population member are used interchangeably) • Sampling frame is the listing of all elements of a population, i.e., a list of all medical students at the university of Jordan, 2014-2016. Sampling

40. Sampling depends on the sampling frame. • Sampling frame: is a listing of all the units that compose the study population. Sampling Methods

41. Primary data. It is the data that has been compiled by the researcher using such techniques as surveys, experiments, depth interviews, observation, focus groups. • Types of surveys. A lot of data is obtained using surveys. Each survey type has advantages and disadvantages. • Mail: lowest rate of response; usually the lowest cost • Personally administered: can “probe”; most costly; interviewer effects (the interviewer might influence the response) • Telephone: fastest • Web: fast and inexpensive Primary vs Secondary Data

42. Secondary data. The data that has been compiled or published elsewhere, e.g., census data. • The trick is to find data that is useful. The data was probably collected for some purpose other than helping to solve the researcher’s problem at hand. • Advantages: It can be gathered quickly and inexpensively. It enables researchers to build on past research. • Problems: Data may be outdated. Variation in definition of terms. Different units of measurement. May not be accurate (e.g., census undercount). Primary vs Secondary Data

43. Response Errors. Data errors that arise from issues with survey responses. • subject lies – question may be too personal or subject tries to give the socially acceptable response (example: “Have you ever used an illegal drug? “Have you even driven a car while intoxicated?”) • subject makes a mistake – subject may not remember the answer (e.g., “How much money do you have invested in the stock market?”  • interviewer makes a mistake – in recording or understanding subject’s response • interviewer cheating – interviewer wants to speed things up so s/he makes up some answers and pretends the respondent said them. • interviewer effects – vocal intonation, age, sex, race, clothing of interviewer may influence response. An elderly woman dressed very conservatively asking young people about usage of illegal drugs may get different responses than young interviewer wearing jeans with tattoos on her body and a nose ring. Survey Errors

44. Probability Sampling Methods. Involves the use of random selection process to select a sample from members or elements of a populations. • Simple Random Sampling • Systematic sampling. • Stratified sampling. • Multistage sampling. • Cluster sampling. Types of Sampling Methods

45. Involves random selection procedures to ensure that each unit of the sample is chosen on the basis of chance • All units of the study population should have an equal or at least a known chance of being included in the sample • Requires a sampling frame • Listing of all study units Probability Sampling Methods

46. This is the simplest of probability sampling • Make a numbered list of all units in the population • Decide on the sample size • Select the required number of sampling units using the lottery method or a random number table Simple Random Sampling

48. Individuals are chosen at regular intervals from the sampling frame • Ideally we randomly select a number to tell us the starting point • every 5th household • every 10th women attending ANC • Sampling fraction = Sample size Study population • Interval size= study population Sample size Systematic Sampling

49. If we have study units with different characteristics which we want to include in the study then the sampling frame needs to be divided into strata according to these characteristics • Ensures that proportions of individuals with certain characteristics in the sample will be the same as those in the whole study population • Random or systematic samples of predetermined sample size will have to be obtained from each stratum based on a sampling fraction for each stratum Stratified Sampling

50. Involves more than one sampling method • Is therefore carried out in phases • Does not require a initial sampling frame of whole population • NEED TO KNOW SAMPLING FRAME OF CLUSTERS E.G. PROVINCES • Require sampling frames of final clusters final clusters • Applicable to community based studies e.g. interviewing people from different villages selected from different areas, selected from different districts, provinces Multistage Sampling