Lesson 4 Flashcards

1
Q

refers to the plan, structure, and strategy of research; the blueprint that will guide the research process.

A

Research Design

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2
Q

Research Design may be developed

A

-to find out the nature of phenomenon,
-to generate a hypothesis of relationship, or
-to test a hypothesis

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3
Q

The test for the quality of the studies research design is the study’s _____

A

conclusion validity

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4
Q

refers to the extent of researcher’s ability to draw accurate conclusions from the research.

A

CONCLUSION VALIDITY

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5
Q

correctness of conclusions regarding the relationships among variables examined.

A

Internal Validity

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6
Q

Generalizability of the findings to the intended/appropriate population/setting

A

External Validity

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7
Q

Guiding principle for effective control of variances (and, thus, effective research design) is:

A

THE MAXMINCON PRINCIPLE
MAXmize systematic variance
MINimize error variance
CONtrol variance of Nuisance/Extraneous/Exogenous/Confounding variables

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8
Q

simulates absence of X

A

CONTROL GROUP

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9
Q

GENERAL METHODS OF DATA COLLECTION:

A

Review of Documents
Query
Observation

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10
Q

This means getting the true value or measurement.

A

Accuracy

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11
Q

ability of the data collection tool to measure what it is supposed to measure

A

Validity

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12
Q

capacity to pick up or label positive those who have the disease.

A

sensitivity

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13
Q

capacity of the test to exclude or label negative those who do not have the disease.

A

specificity

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14
Q

the chance than a positive result is truly indicative of
the presence of the disease or condition.

A

positive predictive value

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15
Q

ability of the tool to give the same or identical results when the test is done on the same subject by different observers. It eliminates observer bias

A

Objective

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16
Q

Ability of the measuring device to give consistent results. Standard deviation or variance measures precision; the greater its value the lower is the
precision

A

Precision, Repeatability or Reliability

17
Q

MAXIMIZING SYSTEMATIC VARIANCE:

A

IN EXPERIMENTS: (where the researcher actually manipulates the independent variable and measures its impact on the dependent variable):
IN NON-EXPERIMENTAL STUDIES: (where independent and dependent variables are measured simultaneously and the relationship between them are examined):

18
Q

MINIMIZING ERROR VARIANCE (MEASUREMENT ERROR):

A

Increase validity and reliability of measurement instruments.
Measure variables under as ideal conditions as possible

19
Q

Sources of error variance:

A

Poorly designed measurement instruments (instrumentation error).
Error emanating from study subjects (e.g., response error).
Contextual factors that reduce a sound/accurate measurement instrument’s capacity to measure accurately.

20
Q

HOW TO CONTROL FOR CONFOUNDING/ NUISANCE VARIABLES:

A

In Experimental Settings:
Conducting the experiment in a controlled environment (e.g., laboratory).
Subject selection (e.g., matching subjects in experiments).
Random assignment of subjects (variations of confounding variables are evenly distributed between the experimental control groups)

In Survey Research:
Sample selection (e.g., including only subjects with appropriate characteristics-using male college graduates as subjects will control for potential confounding effects of gender and education)

21
Q

Effective research design is a function of?

A

✓ Adequate (full range of) variability in values of research variables,
✓ Precise and accurate measurement,
✓ Identifying and controlling the effects of confounding variables, and
✓ Appropriate subject selection

22
Q

Experimental Designs

A

True Experimental Studies

23
Q

Non-Experimental Designs

A

Expost Facto/Correlational Studies

24
Q

One of the simplest experimental designs is the

A

ONE GROUP PRETEST-POSTTEST DESIGN-EXAMPLE

25
Q

be aware of the _______ (it tends to prejudice the results especially in medical research).
SOLUTION: _______ (neither the subjects nor the experimenter knows who is getting the placebo/drug).

A

Experimenter Effect…Double Blind Experiments

26
Q

potential confounding fact in experimental studies:

A

Hawthorne Effect
History: Biasing events that occur between pretest and post-test
Maturation: Physical/biological/psychological changes in the subjects
Testing: Exposure to pretest influences scores on post test
Instrumentation: Flaws in measurement instrument/procedure

27
Q

(regression toward the mean)?
Subjects selected based on extreme pretest values
Discovered by in 1877

A

Statistical Regression

28
Q

Differential drop-out of subjects from experimental and control groups during the study

A

Experimental Mortality

29
Q

Important Features of True Experimental Designs

A
  1. PRESENCE OF A COMPARISON GROUP
  2. RANDOMIZATION
  3. BLINDING
  4. PROGNOSTIC STRATIFICATION
29
Q

Important Features of True Experimental Designs

A
  1. PRESENCE OF A COMPARISON GROUP
  2. RANDOMIZATION
  3. BLINDING
  4. PROGNOSTIC STRATIFICATION
30
Q

At Least Four Other Possible Interpretations/Reasons For Correlations Between Two Variables:

A

Both variables are effects of a common cause
Both var. alternative indicators of same concept
Both parts of a common “system” or “complex;” tend to come as a package
Fortuitous–Coincidental correlation, no logical relationship

31
Q

John Stuart Mill’s Rules for Inferring Causal Links

A
  • Covariation Rule (X and Y must be correlated) - Necessary but not sufficient condition.
  • Temporal Precedence Rule (If X is the cause, Y should not occur until after X).
  • Internal Validity Rule (Alternative plausible explanations of Y and X-Y relationships should be ruled out (i.e., eliminate other possible causes).
32
Q

STEPS IN PLANNING FOR DATA COLLECTION:

A

1.Identify the data to be collected
2.Determine the possible sources of data
3.Choose the method appropriate for the study
4.Prepare the tools of data collection
5.Establish the time-frame of data collection, considering the number of subjects, the time needed to collect the data per subject, and the number of personnel for the work.

33
Q

The plan of data collection includes:

A

✓The data or information to be collected.
✔How information are to be collected including the tools to be used.
✔How quality control is to be ensured and the different forms of bias are to be eliminated. ✓Time table for data collection including how this is estimated.

34
Q

GENERAL METHODS OF DATA COLLECTION:

A

Review of Documents
Query
Observation

35
Q

TOOLS OF DATA COLLECTION:

A
  1. Questionnaire is essential for asking questions.
  2. Devices and tests are needed in the assessment of the outcome of process.
36
Q

CRITERIA FOR CHOOSING THE METHOD OF DATA COLLECTION:

A

✓Accuracy of the information generated by the method.
✓ Practicability of the method