Quantitative Health Research Lecture # 4 Hypothesis and/or Research Questions

1. Quantitative Health ResearchLecture # 4Hypothesis and/or Research Questions Hypothesis and research questions

2. Theory Is a set of interrelated concepts, definitions, and prepositions that present a systematic view of phenomena by specifying relations among variables, with the purpose of explaining and predicting the phenomena. It explains why one event is associated with another event or what causes an event to occur. Concept---- propositional statement----theory Hypothesis and research questions

3. Theoretical and conceptual frameworks • Presents a broad, general explanation of the relationships between the concepts of interest in research study that could be collected from one or more than one theory. • Study hypothesis (es) or questions are based on the propositional statement from the theory or from the theoretical framework the researcher developed. • Hypotheses bring direction, specificity and focus to a research study. Hypothesis and research questions

4. Hypotheses and Research Questions • Hypotheses are ideas or intelligent guesses that assist the researcher in seeking the solution to a problem. • Hypothesis is a tentative proposition. • Its validity is unknown. • In most cases, it specifies a relationship between two or more variables. Hypothesis and research questions

5. Hypotheses and Research Questions • The hypothesis is the starting point of any research and is a tentative prediction or explanation of the relationship between two or more variables. “They are written before the study” • Research studies may have one or several hypotheses. Hypothesis and research questions

6. Hypothesis and Research Questions • While the problem statement presents the question that is to be asked in the study, the hypothesis presents the answer to the question. • The hypothesis links the independent and the dependent variables. • Hypotheses should be: conceptually clear, verifiable, related to existing body of knowledge, and operationalisable (i.e. measurable, can be tested). Hypothesis and research questions

7. Purposes of hypotheses • Test theoretical prepositions; Pinpoint specific part of a theory to be tested. • Guide the research design. • Dictate the type of statistical analysis to be used with the data. • Provide the reader with an understanding of the researcher’s expectations about the study before data collection begins. Hypothesis and research questions

8. Sources or Rationale for Study Hypothesis • Personal experience or observations (inductive) e.g hospital practice and observation • Previous research study: e.g may test the other points of the theory that Was not tested. • Theoretical or conceptual framework testing (Deductive) e.g a part from Maslows theory of human needs. Hypothesis and research questions

9. Hypotheses criteria • Written in declarative form; correlation or comparative statements. • Contains the population. • Contains the variables. • Reflects the problem statement. • Is empirically testable. Hypothesis and research questions

10. Examples: Correlation: Problem: Is there a correlation between anxiety level and midterm examination scores of baccalaureate students? Hypothesis: There is a negative correlation between anxiety levels and midterm examination scores of baccalaureate students. Hypothesis and research questions

11. Comparative: • Problem: Is there a relationship between readiness to understand preoperative teaching between preoperative patients who have high anxiety levels compared to preoperative patients who do not have high anxiety levels? • Hypothesis: Readiness to understand preoperative teaching is less among preoperative patients who have high anxiety levels compared to preoperative patients who do not have high anxiety levels. Hypothesis and research questions

12. Types of Hypothesis A )According to the number of variables: 1.Simple: predicts the relationship between (1) I.V. and (1) D.V. (Bi-variate) 2.Complex: Predicts the relationship between (2) I.Vs, (2) or more D.Vs or both (Multivariate) * Hypothesis are not needed in uni-variate studies (e.g. Frequency chart or table). Hypothesis and research questions

13. Examples 1. Simple: Birth weight is lower among infants of smoking mothers than among infants of non smoking mothers. 2. Complex : More postpartum depression and Feelings of inadequacy are reported by women who give birth by C.S. than by ND. Hypothesis and research questions

14. Note: • It is better to use several simple hypotheses than one complex hypothesis. • When the interaction effect of two or more independent variables is studied, the hypothesis should be complex. Hypothesis and research questions

15. Types of Hypothesis Complex ( Interaction effect ) : Daily weight loss is greater for adults Who follow a reduced caloric intake diet and exercise daily than for those who do not follow a reduce caloric diet and do not exercise daily. Hypothesis and research questions

16. Types of Hypothesis B) According to whether the direction of the relationship is identified or not • Non directional research hypothesis. A relationship exists. • Directional researchhypothesis. The type of the relationship is predicted. A directional hypothesis should contain terms such as: more than, greater than, positive correlation…. Hypothesis and research questions

17. Examples: • Anxiety levels are lower for preoperative orthopedic patients who have practiced relaxation exercises than for those who have not practiced relaxation exercises. • There is a change in the anxiety levels of preoperative orthopedic patients after listening to a relaxation tape. Hypothesis and research questions

18. The Relation between Hypothesis and Problem Statement • Problem statement : Is there a difference in the anxiety levels of preoperative pts after Listening to a relaxation tape? • Non directionalhypoth.: There is a difference in the anxiety levels of preoperative pts after Listening to a relaxation tape. • Directional hypothesis: The anxiety levels of preoperative pts will decrease after listening to a relaxation tape. Hypothesis and research questions

19. The Relation between Hypothesis and Problem Statement • Problem statement : Is there a difference in the anxiety levels of preoperative pts after Listening to a relaxation tape? • Non directionalhypoth.: There is a difference in the anxiety levels of preoperative pts after Listening to a relaxation tape. • Directional hypothesis: The anxiety levels of preoperative pts will decrease after listening to a relaxation tape. Hypothesis and research questions

20. Hypotheses (Recap from last Lecture) Hypothesis and research questions

21. What we discussed so far about Hypotheses • Concept  propositional statement  Theory • Hypotheses vs Research Questions or Problem Statements • Types of Hypotheses • According to # of variables • According to the directions of the relationship between variables • In statistical terms: H0 and H1 or Ha Hypothesis and research questions

22. Hypothesis Testing (Correct Decisions and Errors) Hypothesis and research questions

23. Null vs Alternate Hypotheses • Null Hypothesis (H0) - the “status quo” • Alternate Hypothesis (H1 or Ha) - Research Hypoth. • REMEMBER: Hypotheses are never proved. Theories are never proved. Null hypothesis rejected Research hypothesis supported  Theory supported. • Research questions replace hypotheses in univariate and qualitative studies. Hypothesis and research questions

24. Scenario # 1 • A company has stated that their straw machine makes straws that have 4mm diameter. A worker believes the machine no longer make straws of this size and samples 100 straws to perform a hypothesis test with 99% confidence. • Let’s write H0 and Ha. • H0: µ = 4mm • Ha: µ ≠ 4mm • n= 100 • c= 0.99 • α= 0.01 Hypothesis and research questions

25. Scenario # 2 • Doctors believe that the average teen sleeps on average no longer than 10 hours per day. A researcher believes that teens on average sleep longer. [Remember: In any case, H0 and Ha should encompass the whole range of possible answers.] • Let’s write H0 and Ha. • H0: µ ≤ 10 hours • Ha: µ > 10 hours Hypothesis and research questions

26. Scenario # 3 • The school board claims that at least 60% of students bring a phone to school. A teacher believes this number is too high and randomly samples 25 students to test at a level of significance of 0.02. • .. H0 and Ha. • H0: P ≥ 0.60 • Ha: P < 0.60 • n= 25 • α= 0.02 • c= 0.98 Hypothesis and research questions

27. Errors on Hypothesis Testing REMEMBER: No research study is perfect and all research findings are subject to potential error due to either study design (bias) or chance (random error). Hypothesis and research questions

28. Errors on Hypothesis Testing • Level of significance for rejecting the Null hypothesisis usually set at .05 level. This means the researcher is willing to risk being wrong 5% of the time (or 5 times out of 100) when rejecting the H0. Or, there is a 5% chance of rejecting the null hypothesis when, in fact, it is true. • Rejecting the null hypothesis when it is true is known as a type I error or a false-positive result, and it occurs when an observed difference between study groups is actually due to chance. Hypothesis and research questions

29. Your Statistical Decision True state of Null hypothesis H0 True (example: the drug doesn’t work) H0 False (example: the drug works) Reject H0 (ex: you conclude that the drug works) Type I error (α) Correct Do not reject H0 (ex: you conclude that there is insufficient evidence that the drug works) Correct Type II Error (β) Type I and Type II Error in a box

30. Type I error (alpha error) • Occurs when an experimenter thinks she/he has a significant result, but it is really due to chance • Analogous to a “false positive” on a drug test. • Risk of a Type I error is the same as the significance level, e.g., p < .05 • Solutions: avoid internal validity errors (such as confounding variables), use a stricter significance level, use replication

31. Type II error (beta error) • Occurs when a researcher fails to find a significant result when, in fact, there was something significant going on. • Analogous to a “false negative” on a drug test. • Must be calculated with a test of statistical “power,” e.g., given the sample size, how big would an effect have to be in order to detect it? • Solutions: increase sample size, use more sensitive precise measures, use replication

32. Error and Power • Type I error rate (or significance level): the probability of finding an effect that isn’t real (false positive). • If we require p-value<.05 for statistical significance, this means that 1/20 times we will find a positive result just by chance. • Type II error rate: the probability of missing an effect (false negative). • Statistical power: the probability of finding an effect if it is there (the probability of not making a type II error). • When we design studies, we typically aim for a power of 80% (allowing a false negative rate, or type II error rate, of 20%).

33. Significance Level and Power • The significance level of a hypothesis test is the chance that the test rejects the Null hypothesis, on the assumption that the Null hypothesis is true. • The Power of a hypothesis test against a particular alternative hypothesis is the chance that the test rejects the Null hypothesis, on the assumption that that alternative hypothesis is true.

34. The P-value of a test is the probability that the test statistic would take a valueas extreme or more extreme than that actually observed, assuming H0 is true.

35. Thank you Hypothesis and research questions