Research Midterm Flashcards

1
Q

Logical steps of scientific method

A

Step 1) state problem or pose question

Step 2) form a hypothesis (explanation or possible answer)

Step 3) Test hypothesis

Step 4) Analyze data

Step 5) Draw Conclusions

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2
Q

Independent variable

A

what the researcher wants to study

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3
Q

Dependent variable

A

what the researcher will measure to provide evidence

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4
Q

extraneous variables

A

factors other than the independent variables that can affect the dependent variables

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5
Q

Confounding variables

A

extraneous variables that cannot be controlled for or eliminated from an experiment

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6
Q

Hypothesis vs theory

A

hypothesis

  • prediction of the final outcome of research
  • concrete, specific statement
  • based on deductive reasoning

Theory:

  • belief or assumption about how things relate to each other
  • establishes a cause and effect relationship between variables with a purpose of explaining and predicting phenomena
  • based on inductive reasoning
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7
Q

Inductive reasoning

A
  1. observe: collect info based on one or more examples
  2. Analyze: ID patterns
  3. Infer: create a general rule from observations
  4. Confirm: make more observations to strength inference
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8
Q

inductive reasoning can be used to:

A
  • part to whole: the whole is assumed to be the same as the individual parts (ex. all 10,00 dogs examined had fleas, therefore all dogs have fleas)
  • Extrapolations: areas of study beyond the exact area studied will behave in the same manner (ex. all dogs have fleas, cats are similar to dogs, therefore they must all have fleas)
  • Predictions: future will behave the same as the past
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9
Q

Deductive reasoning

A
  • starts with a rule or law and then deduces specific examples from that law
  • using scientific method, a law can be determined for a specific case and then further testing is done, to show that it holds true in other circumstances
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10
Q

Research Hypothesis

A
  • statement indicating the researchers true expectations as to the outcome of the study, may be the same as or opposite of the null hypothesis
  • expectation as to outcome of the study
  • based on understanding of research problem and analysis of what is known from related literature
  • follows directly after the problem statement
  • never proven, more supported or verified
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11
Q

Statistical hypothesis:

A
  • Null hypothesis: statement indicating expectation of no relationship or no difference for purposes of statistical testing
  • alternate hypothesis: a statement indicating expectation of the researcher that one group differs from another as a function of the independent variable
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12
Q

Compare groups

A
  • treatment groups receives intervention
  • control group receives placebo

Null: groups do not differ on dependent measure

  • treatment and control group score the same on balance test after 10 weeks training

Alternate: groups differ on dependent measure

  • treatment group scores significantly higher than control group - directional alternate hypothesis
  • treatment group scores are significantly different than control group - non-directional alternate hypothesis
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13
Q

reject vs do not reject null

A
  • Reject the null means that real difference exist between the groups (if a = .05 and p = .049, reject the null)
  • Do not reject the null means that no group differences exist ( if a = .05 and p = .52, do no reject the null)
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14
Q

Clinical relevance vs effect size

A
  • often discussed when results of a study are non-significant
  • researchers attempt to make a case for the effect size being large enough that it is likely to be of interest in clinical practice
  • with no objective test for clinical relevance, researchers must make the case with logic
  • can be important when results are statistically significant but the effect size is small
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15
Q

types of research

A

basic, applied, translational

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16
Q

Basic research:

A
  • conducted purely for discovery of new knowledge, with little regard for whether there is an immediate application for that new knowledge
  • pure, fundamental research
  • theoretical in nature
  • takes many years for the results to find practical utility
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17
Q

Applied research:

A
  • driven by need to find a solution to a specific problem
  • improved products or processes
  • infers beyond group or situation studied
  • interpretation of results relies upon basic research
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18
Q

Translational research:

A
  • specific to studies in which a finding from basic is first investigated in humans
  • common for research related to clinical applications to start with animal subjects to ensure safety
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19
Q

Quantitative vs qualitative

A

Quantitative research:

  • dependent variable are numbers
  • tradition or positivist approach
  • clearly stated questions, rational hypothesis
  • developed research procedures

Qualitative research:

  • dependent variable are quality (descriptions)
  • typically anthropological and sociological research methods
  • observations of a natural setting
  • in-depth descriptions of situations
  • interpretive and descriptive
20
Q

Experimental vs non-experimental

A

Experimental:

  • investigator provides treatment or intervention
  • confirms or refutes cause-effect relationships
  • aims at achieving understanding
  • involves measuring effects of independent variable on dependent variables to determine a mechanism

Non-experimental:

  • no treatment or intervention
  • cannot speak to cause and effect
  • aims to provide a detailed, useful description of characteristics of a population, group, or individual
  • is often hypothesis generating
21
Q

Cause-effect relationship

A
  • strong correlation between the cause and effect
  • the cause precedes the effect
  • cause always produces the effect
  • there is not a viable alternative explanation for the effect
  • independent variable is the cause and dependent variable is the effect
22
Q

Experimental research designs

1) Single-subject research (not a case study)

A
  • use when there is a high degree of individual variability in performance
  • single or small group of participants
  • unlike case study, researchers provide an experimental intervention or treatment
23
Q

Experimental research designs

2) Pre-experimental designs

A
  • weak designs
  • no random assignment of participants to groups
  • little control of threats to validity
  • sometimes used due to practical constraints
24
Q

Experimental research designs

3) True experimental designs

A
  • require random assignment of participants to groups
  • control many threats to internal validity, including history, testing, stats regression, selection bias
  • referred to as randomized control trials or RCT
25
Q

Experimental research designs

4) Quasi-experimental designs

A
  • designed to optimize external validity

- used when circumstances prevent random assignment of participants to groups

26
Q

non-experimental/descriptive methods

A
  • patterns and trends in relationships among individual characteristics and specific disease or health conditions
  • data acquired through survey or existing data bases (no intervention)
  • large # of participants used
  • can answer questions like “does obesity status lead to higher rates of cancer?”
27
Q

Analytic vs descriptive

A

analytic descriptive research:

  • no intervention
  • describes patterns and trends, but quantifies the relationship or association between variables
  • quantitative research

Non-analytic descriptive research:

  • no intervention
  • describes patterns and trends without numerical data
  • qualitative research
28
Q

Non-experimental research designs

1) Cohort study (analytic)

A
  • Prospective: how does current exposure lead to outcome disease in the the future? (looks forward)
  • select diverse groups from population who vary in exposure to risk factor
  • follow groups over substantial period of time, periodically checking for outcome
  • no direct intervention
  • quantifies the probability of developing disease based on exposure to determinants: relative risk
29
Q

Non-experimental research designs

2) Case control study (analytic)

A
  • Retrospective: given current disease or health state, what was exposure in the past? (looks backwards)
  • create groups with (case) and without (control) disease state
  • survey groups on past exposure to risk factors
  • quantifies odds of developing health condition based on inclusion in case of control and exposure to risk factor: odds ratio
30
Q

Non-experimental research designs

3) Cross-sectional study (analytic)

A
  • observes current occurrence of disease or condition in a given population
  • “snapshot”
  • quantifies disease prevalence
31
Q

Non-experimental research designs

4) Epidemiological research (analytic/non-analytic)

A
  • study of determinants of incidence, distribution, spread, and control of disease and health
  • “why are some people healthy and other are not?”
  • can be similar to both case control or cohort studies but is often more generalized
32
Q

Non-experimental research designs

5) Case study (non-analytic)

A
  • single-subject report

- often seen in medical journals for unique & interesting condition or first occurrences of a treatment

33
Q

Non-experimental research designs

6) correlational research (analytic/non-analytic)

A
  • form of non-experimental or descriptive research
  • conducted to evaluate statistical relationship between two or more variables
  • sometimes conducted for purposes of prediction or hypothesis generation
34
Q

empirical vs theoretical research

A

empirical:
- collects data
- uses observations/measurements to create new ideas
- experimental
- follows scientific method

theoretical:

  • uses knowledge and logic to create hypothetical idea
  • ideas are not tested in lab
  • exmaples include math modeling and proofs
35
Q

primary vs secondary research

A

primary:
- collection of new data or creation of new idea

secondary:

  • uses previously collected data to make generalizations and/or to strengthen current understanding of topic
  • descriptive reviews, systematic reviews, meta-analyses
36
Q

validity definition

A

ability of research study or instrument to faithfully reflect true state of variables being studied in the population of interest

37
Q

internal vs external validity

A

Internal validity:

  • ability to conclude that only the independent variables affected any differences in measures of the dependent variables across groups or across test on the same group
  • is a measure of the success of efficacy of the effect of the experiment

External validity:

  • ability to apply results of a study to the sample population in a real world setting
38
Q

Threats to internal validity

A
  • *History**: something occurring over time that could affect the dependent variables
  • *Maturation**: effects related to the passage of time, such as aging
  • *Testing**: beneficial practice effects for repetitions of the same test
  • *Instrumentation**: negative effects of reliability problems with equipment or observers
  • *Statistical regression**: tendency of extreme scores to regress toward the mean upon retest
  • *Selection bias**: comparison groups are not equal at the beginning of the study
  • *Experimental mortality**: loss of participants from a study (for any reason)
  • *Selection-maturation interaction**: maturation affects groups within the study differently
  • *Expectancy**: rater expectations influence data
39
Q

Threats to external validity

A

Interaction effect of testing: pretest changes the group’s response to experimental treatment

Interaction of selection bias and experimental treatment: biased sample produces skewed results not representative of population

Reaction effects of experimental setting: some element of setting causes modification of participant behavior

Multiple treatment interference: experiencing one treatment affects participant response to a subsequent treatment

40
Q

Ecological validity

A
  • extent to which testing conditions in a study are like conditions in the environment being studied
  • another component of external validity
41
Q

Types of Reliability

A

Test/Retest: use the same test on the same group of subjects more than once and compare

Parallel Forms: compare the equivalence of two tests that measure the same thing

Internal consistency: measure of how well each individual item of the test represents the whole test

42
Q

Sampling

A
  • who we include in study

- how they are chosen

43
Q

Importance of sampling

A
  • goal is to collect data from participants in research study and to be able to generalize the findings to the larger population that the participants represent
  • Used to answer two types of questions:
  • 1) is there a relationship between variables?
  • 2) is there a difference across conditions?
44
Q

Sample size

A
  • large enough to be representative of population
  • small enough to enable practical collection of data from the standpoint of time & resources
  • often calculated to arrive at a power level of 0.8, where power is the probability of correctly rejecting the null hypothesis when it is false
45
Q

sampling techniques

A

1) random selection: all members of the population have equal chance of being selected
2) stratified random: all members of designated subgroups have equal chance
3) stratified proportional: equal proportion of each subgroup is randomly selected
4) systematic: every nth individual on a list is selected
5) convenience: qualified readily available selected
6) cluster: population is separated into groups then a sample of clusters is selected

46
Q

Sampling criteria

A

inclusion criteria:

  • characteristics individuals must possess to qualify for participation in a research study

Exclusion criteria:

  • characteristics individuals must NOT posses to qualify for participation in a research study
47
Q

Ideal study design

A
  • sample is representative of pop of interest
  • groups of samplers are as close to identical as possible at the start of the experiment except for the treatment being applied