Brainscape's Knowledge GenomeTM


Top Flashcards (Certified)
All Flashcards

CU: Research Methods > Final Exam Material > Flashcards

Final Exam Material Flashcards

(90 cards)

Start Studying
1
Q

What is the definition of statistics? What are the two classifications?

A

Procedures for collecting, analyzing, interpreting, and presenting data
1) Descriptive Statistics
2) Inferential Statistics

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

What is the definition of descriptive statistics? An example?

A

Used when measuring characteristics of a group without intending to generalize beyond the group
Example: Mean +_ SD: age, BMI, height

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

What is the definition of inferential statistics? An example?

A

Used when making generalization s or inferences from a smaller group (sample) to a larger group (population)
Examples: t-test or ANOVA, correlations: Person’s Correlation Coefficient, Simple Linear Regression, & Multiple Regression

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

What is the definition of a population? What is the value representing a characteristic of the population?

A

A large group to which the results of a study conducted on a sample from the group may be generalized
Value: parameter

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

What is the definition of a sample? What is the value representing a characteristic of the sample?

A

Individuals from the population who actually participate in the research –> a representative subset of the population
Value: statistic

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

What is a sampling frame?

A

A list of all those within a population who can be sampled (sample is taken from this)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

What are the steps in sampling?

A
  1. Define the population by specifying the criteria (inclusion and exclusion) for selecting participants
  2. Develop the plan for sample selection
  3. Determine the sample size (power analysis?)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

What are the options for sample selection?

A

Random Sampling
- Simple Random Sampling
- Systematic Random Sampling
- Cluster Random Sampling
- Stratified Random Sampling
Non-Random Sampling
- Convenience (Volunteer) Sampling

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

What is the definition, advantage, and disadvantage of simple random sampling?

A

Every person in the population has an equal chance of being selected for the sample
- Advantage: unbiased, representative sample
- Disadvantage: Need a good sampling frame

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

What is the definition, advantage, and disadvantage of systematic random sampling?

A

Every nth person from sampling frame is selected to participate
- Advantage: easier to administer than simple random sampling
- Disadvantage: may be biased if pattern in population

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

What is the definition, advantage, and disadvantage of cluster random sampling?

A

Specific clusters (groups) are randomly selected out of all possible clusters
- Advantages: time- and cost-effective (convenient and practical), large samples
- Disadvantages: May be biased/non-representative if clusters are different from each other

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

What is the definition, advantage, and disadvantage of stratified random sampling?

A

Members of the sampling frame are divided into subgroups (strata)
- Random sample of participants then selected from each strata
- Advantages: Good representative sample: captures key characteristics of the population
- Disadvantages: Difficult to administer, need detailed information about the population

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

What is the definition, advantage, and disadvantage of convenience sampling?

A

Investigators recruit easily available individuals who meet criteria until meet desired sample size
- Advantage: very convenient
- Disadvantage: sample may be biased, self-selection bias

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

What type of sample selection is a survey of admissions of individuals with Type II diabetes to hospitals in greater Dayton area?

A

Cluster

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

What type of sample selection is a study of risk factors for progression of osteoarthritis (assuming more women affected than men)?

A

Stratified

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

What type of sample selection is a study of rural access to health care in the different regions of Ohio?

A

cluster

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

What type of sample selection is a survey of of satisfaction and retention among PA in Ohio?

A

Simple or systematic

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

What type of sample selection is a study of the effectiveness of resistance training on functional outcomes in patients with chronic obstructive pulmonary disease?

A

Convenience

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

What is the difference between random selection vs random assignment?

A

RS: about how elected: more representative more generalizable
RA: making groups: more equal = good internal validity, better for causality

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

What are the types of frequency distributions?

A
  • Normal distribution: symmetrical bell-shaped curve
  • Non-Normal distribution: highest frequencies of scores do not fall centrally but are shifted towards positive or negative extremes
    (positively, negatively skewed: where the tail is)
  • Kurtosis: a vertical shift in the normal curve; the middle of the curve is elevated or flattened
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

What are the two aspects of descriptive statistics?

A

Measures of central tendency: mean, median, mode
Measures of variability: range, standard deviation, variance, standard error of the mean (SEM)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
22
Q

What are the measures of central tendency?

A

Extent to which values cluster in a data distribution plot
- Mean: the average of all the number
- Median: middle number in the list
- Mode: most frequently occurring number
Normal distributions: use mean
Skewed distributions: use median

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
23
Q

What are the arrangement of skewed distributions?

A

Positively: mode < median < mean
Negatively: mean < median < mode

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
24
Q

What are the measures of variability? (Elaborate on the first two)

A

How the scores vary; how they are dispersed around the measures of central tendency
- Range: the difference between the highest and lowest scores (ie age range)
- Standard deviation: a numerical indicator of the spread of values within a data set
- Variance
- Standard Error of the Mean

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
25
What could a large standard deviation around the mean indicate?
- wide spread of data - indicate outliers - sample size too small
26
What is variance?
The square of the standard deviation; used to calculate many other statistics
27
What is the standard error of the mean? What makes it smaller and what does this mean?
an estimate of the expected difference between the sample mean and the population mean. (SEM = SD/ square root of n) Smaller standard deviation, larger sample size the smaller the SEM The smaller the SEM the **greater** the confidence that the sample mean accurately **represents** the population mean.
28
What is the sampling error?
The difference between a calculated sample mean and the (unknown) population mean
29
Which hypothesis is typically tested in inferential statistics?
The null hypothesis
30
If the level of significance is 0.05 what does this mean for the chance that the study results are erroneous? What does it mean for the researcher's confidence?
5% chance of the study results being in error 95% confident they will detect a true difference when there is one
31
When is a alpha level of 0.01 or 0.001 selected?
Medical interventions, pharmacutical companies
32
What is the p value?
The probability value--calculated by the computer. The probability of the results being due to chance--measure of the strength of evidence against the null hypothesis. Low: strong evidence against null High: weak evidence against null
33
In clinical studies what are the concerns of type I and type II errors?
Type I: pts treatment does not actually work Type II: treatment was effective but was rejected and is no longer available
34
What is the B level typically?
0.2 (20%)
35
What is the most common reason for a type II error?
small sample size causing low power
36
What is the trade off of level of significance and type I and II errors?
Lower alpha decreases risk of Type I error and increases risk of Type II.
37
What is the power of a study? What does it mean if it is high? What is the equation? What is the typical level in health research? What kind of sample size is important for adequate power?
The probability of making a correct decision regarding the null hypothesis. - High: will correctly detect statistically significant differences when they do occur - Power = 1 - B - Typically 0.8 (80%) - Large enough sample size
38
What are the assumption s of parametric statistics?
- normal distribution - homogeneity of variance - interval or ratio (continuous) data
39
When are non-parametric statistics used?
- not normally distributed - small sample size - nominal or ordinal level data
40
What is Levene's Test for Equality of Variances?
if the p value is > 0.05 the variances are not significantly different and equal variances are assumed
41
What is a t Test used for?
To compare **two** groups on one dependent variable
42
What is ANOVA and what is it used for?
Parametric statistic used to compare the means of - more than 2 groups - 2 groups at multiple points in time - 1 group with 3 or more time points (see if they are different or not)
43
What are the ANOVA assumptions?
- normal distribution - homogeneity of variance - interval or ratio (continuous) scales
44
What is the One-way ANOVA?
- One independent variable/factor - Three or more levels (groups) - Testing the null hypothesis (no difference)
45
What is the statistic calculated from an ANOVA? What does it represent? What about the p value?
Statistic: F ratio Between group variance (b/c treatment variable) / Within group variance (b/c error) p value: chance probability of F ratio
46
What is the Post Hoc test? Why is it used?
Determines where differences exist. Used **if** the one-way ANOVA produces a **significant** F-ratio (at least one group is different)
47
What is the Two-Way (factorial) ANOVA?
Study effect of **more than one independent variable** on a dependent variable (2x2) determines: 1) **Main** effect of Variable A alone 2) **Main** effect of Variable B alone 3) **Interaction** (joint) effect of Variable A and B
48
What are the plots of a Two-Way (factorial) ANOVA?
No interaction effect: parallel (near parallel) lines Interaction effect: Nonparallel or intersecting lines
49
What are repeated measures ANOVAs used for? Note?
1) changes in mean scores over: three or more time points 2) differences in mean scores under: three or more different conditions *Present conditions in random order to prevent order effects (practice/fatigue)
50
What is correlational research? (category, investigation of what & how shown, questions)
- type of descriptive research - systematic investigation of **relationships** (correlation/association) among two or more variables - "Do the variables change together in a predictable way?" - **scatter plots** show the variable relationship *Person Correlation coefficient, simple linear regression, multiple regression*
51
What is a positive correlation?
One variable increases as the other variable increases
52
What is a negative correlation?
One variable increases as the other variable decreases
53
How is the strength of a correlation determined?
Line of best fit: degree to which the values in a scatter plot cluster around a line running through them from -1.0 to +1.0
54
What does finding a correlation not mean?
causation only that they are related
55
What is the most common parametric correlation statistic?
Person product-moment correlation coefficient (Person's r) for the relationship between two variables
56
What are the assumptions for a Pearson correlation?
- normal distribution - linear relationship - interval or ratio (continuous) level - no outliers
57
What are the guidelines for interpretating Person's r values?
0.8 and > Very strong 0.6-0.8 Strong 0.4-0.6 Moderate 0.2-0.4 Weak 0.0-0.2 Very Weak
58
How is the significance of a correlation coefficient determined?
By a **test of significance** (random error or good estimate) null: there is no correlation, correlation coefficient = 0 *Significant correlation does NOT necessarily mean there is a strong correlation just that the results are not likely due to chance
59
When is analysis of covariance (ANCOVA) used as a statistical test in research studies? (skip)
When it is known that the group means are different at the beginning of an experiment.
60
What is the nominal level of measurement?
Lowest level: Categories by name or label Example: Gender, Handedness
61
How is the ordinal level of measurement different from the nominal level? Give two examples of the ordinal level of measurement.
It is also non-numerical data but it can be put into an order (spacing may not be equal) Ordered Ranking Examples: Likert Scales (attitudes, preferences), Manual muscle testing (Graded from 0-5)
62
How is the interval level of measurement different from the ordinal level? Give one example of the interval level of measurement.
Numeric measures with ordered rankings of equal distances/intervals between units of measurement Example: Temperature scale
63
How is the ratio (continuous) level of measurement different from the interval level? Give two examples of the ratio (continuous) level of measurement.
Numeric measures with ordered rankings, equal spacing between adjacent numbers and a true zero Examples: walking speed, height
64
Which level of measurement tends to provide more information and allow for more sophisticated statistical analyses than the other levels of measurement?
Ratio (continuous) measurement
65
Independent Variable:
Cause - variable that the researcher manipulates; the experimental treatment
66
Dependent Variable:
Effect - variable being measured to determine the effects of the independent variable
67
What is experimental research designed to do?
establish a cause-effect relationship between an independent variable and a dependent variable
68
What are the three classifications of experimental research?
1) True Experimental 2) Quasi Experimental 3) Pre-experimental
69
What are the three essential characteristics of true experimental research?
1) Manipulation of an independent variable 2) Control (alternative) groups 3) Random Assignments to Groups
70
What is the purpose of random assignments to groups?
- Each participant has an equal chance of being assigned to any group - Increases the likelihood that the groups will be equivalent on key characteristics at baseline - Controls for most threats to internal validity. - Researchers must still do best to minimize the threats of history, instrumentation, and mortality
71
What are the types of true experiment designs and their symbols?
Control group: G1: R D1 T D2 G2: R D1 D2 Two Group: G1: R D1 T1 D2 G2: R D1 T2 D2 Multi-Group: G1: R D1 T1 D2 G2: R D1 T2 D2 G3: R D1 D2
72
Why do some True Experiments have only a post-test design? What’s the concern?
- Want to know response to something can only test for it after have intervention - Concern: Cannot do a statistical test to affirm group equivalency
73
What are the characteristics of Quasi-Experimental Research Designs?
1. No random assignment (already in groups) 2. Control Group OR multiple measures
74
What are the types of Quasi-Experimental Research Designs?
1. Nonequivalent Control Group Design 2. Repeated Measures Design 3. Time Series Design
75
What is the symbol pattern, use, and major threat/minimization strategy to internal validity for nonequivalent control group design?
G1: D1 T1 D2 G2: D1 T2 D2 - Use: When person-factors (IQ, personality, habits) are the independent variable: not ethical or feasible to manipulate - Threat: Selection Bias - Minimize: match groups by relevant variables and statistically compare
76
What is the symbol pattern, use, and major threat/minimization strategy to internal validity for repeated measures design?
T1–D1–T2–D2–T3–D3 (each person becomes own control) - Use: small sample size - Testing - Minimized: allow for adequate rest between exercises, randomized order of tests
77
What is the symbol pattern, use, and 2 major threats/minimization strategy to internal validity for Time Series Design?
D1 D2 D3 {Pre-test} T D4 D5 D6 {Post-test} - Use: See change overtime, effect of policies or rules - Threat: History & instrumentation - Hard to control for
78
How do quasi experiments relate to external/internal validity? Why?
Tend to have stronger external validity (occurs in real-world situations) Tends to have weaker internal validity (due to lack of randomization)
79
What are strategies to reduce internal validity threats in Quazi-Experimental tests.
1) Matched Groups 2) Test (statistically) for group equivalence 3) Larger groups
80
What does simple linear regression do?
Estimates how **variable X** (predictor variable) predicts **variable Y** (criterion variable)
81
What is r2 (squared)?
Gives indication of accuracy of prediction of simple linear regression - How much of the variance in Y is accounted for by knowing X
82
What is multiple regression used for?
To **predict** a criterion (dependent variable) from **two or more** predictor variables (independent variables)
83
What is multiple correlation?
R: calculated as correlation of two or more predictor variables with criterion variable.
84
What is R2 (squared)?
the effect of each variable of a multiple regression in explaining variance in the criterion
85
What questions must be answered to select an appropriate statistical test?
1. Is the research question focused on a **relationship** between variables or a **difference** between groups (cause-effect)? 2. How many **groups** of participants are involved? 3. If there are two groups only, are they **independent** of each other or **related**? 4. How many **independent** variables make up the study? 5. Are there **multiple** measures of the dependent variable?
86
What is a common principle for dealing with drop outs?
Intention to treat. Evaluate all data even if drop outs happen
87
What does clinical meaningfulness mean? How is it assessed?
The practical importance of a treatment effect; whether it has a noticeable effect on daily life Assessed by: - effect size - minimal detectable change (MDC) - minimal clinically important difference (MCID)
88
What is effect size? (calculated from, guidelines)
- **strength** of a treatment effect - indication of the **meaningfulness** of results Calculated from sample means and standard deviations > 0.8 Large 0.5-0.8 Moderate 0.2-0.5 Small < 0.2 weak
89
What is MDC?
Minimal detectable change **smallest change** in a score on an *outcome measure* that likely reflects **true change** Calculated using statistical data, including SEM
90
What is MCID?
Minimal Clinically Important Difference **smallest change** in score on an *outcome measure* that is **perceived to be beneficial by the patient** Calculated by different methods: (SD, SEM, ES)

CU: Research Methods (8 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2025 Bold Learning Solutions. Terms and Conditions