Rd Exam - Domain Iii - Research

Front 1

Begin the research by stating the ______ of the work

Back 1

Problem

Front 2

Null Hypothesis

Back 2

No relationship within the population of Data

And differences are due to sampling error.

Front 3

Steps of Research

Back 3

State Problem
Lit Review
Select Methdology
Oranganize Methods & Materials
Collect and Analyze data

Front 4

Discussion

Back 4

intrepretation of results, compare to tother studies

Front 5

Conclusion

Back 5

Brief summary results may have recommendations

Front 6

Descriptive Research

Back 6

Describes the state of nature at A POINT IN TIME

Used to generate hypothesis

Front 7

DESCRIPTIVE RESEARCH

Surveys

Back 7

describe and quantify characteristics of a population

Front 8

DESCRIPTIVE RESEARCH

Case Report / Case Study

Back 8

Quantitatively describes the experiences of a group.

Front 9

DESCRIPTIVE RESEARCH

Establishes _____ but does not determine _______.

Back 9

Establishes associations but does not determine causal relationships

Front 10

DESCRIPTIVE RESEARCH

Provides ____ Data

Back 10

Provides BASELINE data

Front 11

Analytical Research

Back 11

Includes Experimental Designs(Clinical Trials) & Observational Designs (Co-hort, follow-up, case control)

Front 12

ANALYTICAL RESEARCH

Experimental Model

Back 12

Uses both experimental and control groups

Front 13

ANALYTICAL RESEARCH

Randomization

Back 13

principle of dividing people into groups without bias

Front 14

ANALYTICAL RESEARCH

Placebo removes the possibility of the _________ effect.

Back 14

Placebo removes the possibility of the Hawthorne effect; Positive response due to the attention that participates receive in the study

Front 15

ANALYTICAL RESEARCH

Experimental is successful if...

Back 15

the experiemental group improves more than the control group

Front 16

ANALYTICAL RESEARCH

Quasi-experiemtetal design

Back 16

Time Series - Measurements at periodic intervals before the program begins and after the program ends.

Can show if the results are due to continuation of previous patterns or a noteworthy change.

Multi Time series - uses a control group.

Front 17

ANALYTICAL RESEARCH

Cohort (longitudinal/incidental)

Back 17

Any group members who members have something in common.

(Healthy people over time to see if the develop a disease)

Front 18

ANALYTICAL RESEARCH

Cohort - (Prospective)

Back 18

Being with suspected disease precursors (future-oriented)

Front 19

ANALYTICAL RESEARCH

Case Control

Back 19

Focus on specific disease

Diseased group compared to group without disease (control)

Objective to discover why or how disease occurs

Front 20

ANALYTICAL RESEARCH

Cross-Sectional studies

Back 20

Snap-shop in time

(Prevalence study)

Front 21

Validitiy

Back 21

Ability to measure what it intends to mesaure

Front 22

VALIDITY

Internal, External, Accuracy

Back 22

Internal - The difference between the 2 groups is real

External - tests if you can generalize results to a larger population

Accuracy is a quantitative measurement of taest validity
(systematic errors)

Front 23

VALIDITY

ANOVA

Back 23

Analysis of Variance

Asks if difference of samples is a reliability to be repeated

Compares variance within groups to variance between grups

Front 24

Reliability

Back 24

The reproducability of the results (consistency)

Front 25

RELIABILITY

Parallel Forms, Split-Halves

Back 25

Parallel Forms - Two separate but simiar forms of the test at the same time (coincide scores)

Split Halves - Divide the test in half

Front 26

Sensitivity & Specificity

Back 26

Sensitivity - proportion of those who TEST POSITIVE

Specificity - Those who Test NEGATIVE

Front 27

RELIABILITY

Precision

Back 27

Quantitative measurement of test reliability - Measures random errore

Front 28

VARIABLES

Nominal, Rank order, Numerical discrete, numerical continous

Back 28

Nominal - No special order
Rank Order - Worst to least
N. Discrete - data with numbers
N. Continous - Underlying continous scale (Blood Pressure,age, weight)

Front 29

VARIABLE

Dependent vs. Independent

Back 29

Dependent outcome is the outcome.

Independent variables are manipulated. (treatment for disease, oven temperature)

Front 30

SAMPLING

Non-Probability vs Probability

Back 30

Non-Prob - no way of forecasting for each element in the population sample

Probability that specific segments will be represented

Front 31

Standard Deviation

Back 31

Indicates degree of dispersino about the mean value distribution

Front 32

STANDARD DEVIATION

2/3 (68%) lie within ___ SD of the mean

95% lie within ___ SD of the mean

Back 32

68% lie within ONE standard deviation

95% lie within TWO standard deviation

Front 33

r = the linear correlation coefficient

Back 33

the closer the points the stronger the degree of linear relationship

Front 34

r numbers of correlation

Back 34

+1 (Perfect Positive) Right Slope
-1 (Pefect Negative) Left Slope

0.0 - 0.4 Weak
0.7-0.9 Strong

Front 35

Skews

Back 35

Positively skewed (Moral worth of humanity)

Front 36

p Values

Back 36

P < 0.05 Significant
P < 0.01 Very Significant
P < 0.0001 Very, Very Signficant

P > 0.05 Not Very Significant

Front 37

Descriptive Statistics vs. Inferential Statistics

Back 37

Descriptive - Summarizes and describes aspects of a set of Data

Inferential - conclusions beyond an immediate data set

Front 38

Chi Square Test

Back 38

Tests whether there is a real difference between categories

Front 39

T Test

Back 39

Significant between 2 populations

Null against alternative hypotheseis.