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DPT 673 - Research Statistics > Final > Flashcards

Final Flashcards

1
Q

Research Statistics Final Review

  • Independent groups
  • Two levels of IV
  • Has met assumptions for parametric tests

What test = ?

Purple

A
  • Independent groups
  • Two levels of IV
  • Has met assumptions for parametric tests

What test = Unpaired T-Test

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2
Q

Research Statistics Final Review

  • Independent groups
  • Two levels of IV
  • Has NOT met assumptions for parametric tests

What test = ?

Purple

A
  • Independent groups
  • Two levels of IV
  • Has NOT met assumptions for parametric tests

What test = Man-Whitney U

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3
Q

Research Statistics Final Review

  • Independent groups
  • Three + levels of IV
  • Has met assumptions for parametric tests.

What test = ?

Purple

A
  • Independent groups
  • Three + levels of IV
  • Has met assumptions for parametric tests.

What test = IG NOVA

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4
Q

Research Statistics Final Review

  • Independent groups
  • Three + levels of IV
  • Has NOT met assumptions for parametric tests.

What test = ?

Purple

A
  • Independent groups
  • Three + levels of IV
  • Has NOT met assumptions for parametric tests.

What test = Kruskal-Wallis ANOVA

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5
Q

Research Statistics Final Review

  • Repeated measures
  • Two levels of IV
  • Has met assumptions for parametric tests.

What test = ?

A
  • Repeated measures
  • Two levels of IV
  • Has met assumptions for parametric tests.

What test = Paired T-Test

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6
Q

Research Statistics Final Review

  • Repeated measures
  • Two levels of IV
  • Has NOT met assumptions for parametric tests.

What test = ?

Purple

A
  • Repeated measures
  • Two levels of IV
  • Has NOT met assumptions for parametric tests.

What test = Wilcoxon Signe-Rank

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7
Q

Research Statistics Final Review

  • Repeated measures
  • Three + levels of IV
  • Has met assumptions for parametric tests.

What test = ?

Purple

A
  • Repeated measures
  • Three + levels of IV
  • Has met assumptions for parametric tests.

What test = RM ANOVA

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8
Q

Research Statistics Final Review

  • Repeated measures
  • Three + levels of IV
  • Has NOT met assumptions for parametric tests.

What test = ?

Purple

A
  • Repeated measures
  • Three levels + of IV
  • Has NOT met assumptions for parametric tests.

What test = Friedman’s ANOVA

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9
Q

Research Statistics Final Review

probability of Type I error = ?

Purple

A

alpha: probability of Type I error

  • Set BEFORE the study

t-Test assumptions

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10
Q

Research Statistics Final Review

probability of Type II error = ?

Purple

A

beta: probability of Type II error

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11
Q

Research Statistics Final Review

calculated probability of Type I error = ?

A

p-value: calculated probability of Type I error

  • AFTER the study
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12
Q

Research Statistics Final Review

calculated value for t-test = ?

Purple

A

t Statistic: calculated value for t-test

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13
Q

Research Statistics Final Review

calculated value for ANOVA = ?

Purple

A

F Statistic: calculated value for ANOVA

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14
Q

Research Statistics Final Review

equal variances for RM ANOVA = ?

A

Mauchly’s W: equal variances for RM ANOVA

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15
Q

Research Statistics Final Review

correlation coefficient = ?

(what letter?)

A

r: correlation coefficient

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16
Q

Research Statistics Final Review

effect size for t-test = ?

A

Cohen’s d: effect size for t-test

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17
Q

Research Statistics Final Review

effect size for ANOVA = ?

A

Eta squared: effect size for ANOVA

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18
Q

Research Statistics Final Review

reliability for continuous data = ?

A

ICC: reliability for continuous data

  • Unitless
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19
Q

Research Statistics Final Review

reliability for categorical data = ?

A

Kappa: reliability for categorical data

  • Unitless
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20
Q

Research Statistics Final Review

measure of internal consistency = ?

A

Cronbach’s alpha: measure of internal consistency

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21
Q

Research Statistics Final Review

Point Estimate

VS.

Confidence Interval

A

Point Estimate: a single value that represents the best estimate of the population value

Confidence Interval: a range of values that we are confident contains the population parameter

  • Width concerns the precision of the estimate
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22
Q

Research Statistics Final Review

Correct interpretation of a 95% CI = ?

A

Correct interpretation of a 95% CI?

  • If we were to repeat sampling many times, 95% of the time our confidence interval would contain the true population mean.

Incorrect interpretation of a 95% CI

  • There is a 95% probability that a given measurement falls within a confidence interval.
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23
Q

Research Statistics Final Review

Independent Groups:

t = Difference between means / Variability within groups

What does this mean?

A

Independent Groups

t = Difference between means / Variability within groups

Difference between means:

  • Represents all the possible reasons groups could be different, including treatment effects and error.

Variability within groups:

  • Difference explained by error alone

Error = all sources of variability that CANNOT be explained by the IV.

24
Q

Research Statistics Final Review

Repeated Measures:

t = Mean of difference between pairs / Std. error of the difference scores

What does this mean?

A

Repeated Measures

t = Mean of difference between pairs / Std. error of the difference scores

Mean of difference between pairs:

  • Represents all the possible reasons groups could be different, including treatment effects and error.

Std. error of the difference scores:

  • SD (of mean differences) divided by square root of sample size. Variance assumed equal.
25
Q

Research Statistics Final Review

Null value = 0

  • = ?

Confidence Interval Null Values

A

Null value = 0 = there can be negative values

  • Between group or within group differences
  • Correlations
26
Q

Research Statistics Final Review

Null value = 1

  • = ?

Confidence Interval Null Values

A

Null value = 1, there will be no negative values

  • Relative Risk
  • Odds Ratio
  • Likelihood Ratios
27
Q

Research Statistics Final Review

Normal distribution, Yes = ?
Normal distribution, No = ?

t Test Assumptions

A

Normal distribution, Yes = parametric
Normal distribution, No = Non-parametric

No multiple comparison for t-Test

28
Q

Research Statistics Final Review

Equal variances, Yes = ?
Equal variances, No = ?

t Test Assumptions

A

Equal variances, Yes =

  • Independent Groups (levene’s is NOT significant p>.05) = interpret p-value
  • Repeated measures = N/A = interpret p-value

Equal variances, No =

  • Independent Groups (levene’s IS significant p<.05) = adjust and interpret p-value
  • Repeated measures = N/A = interpret p-value

No multiple comparison for t-Test

29
Q

Research Statistics Final Review

Interval / Ratio DV, Yes = ?
Interval / Ratio DV, No = ?

t Test Assumptions

A

Interval / Ratio DV, Yes = Parametric

Interval / Ratio DV, No = Non-parametric

No multiple comparison for t-Test

30
Q

Research Statistics Final Review

Normal distribution, Yes = ?
Normal distribution, No = ?

ANOVA Assumptions

A

Normal distribution, Yes = Parametric

Normal distribution, No = Non-parametric

31
Q

Research Statistics Final Review

Equal Variances, Yes = ?
Equal Variances, No = ?

ANOVA Assumptions

32
Q

Research Statistics Final Review

Interval/Ratio DV, Yes = ?
Interval/Ratio DV, No = ?

ANOVA Assumptions

33
Q

Research Statistics Final Review

IndependenT Groups

  • (a) Fisher’s Least Significant Difference
  • (b) Tukey’s honestly Significant Difference
  • (c) Bonferroni t-Test
A

IndependenT Groups

  • Tukey’s honestly Significant Difference
34
Q

Research Statistics Final Review

Repeated MeasureS

  • (a) Fisher’s Least Significant Difference
  • (b) Sidak’s Multiple Comparison
  • (c) Bonferroni t-Test
A

Repeated MeasureS

  • Sidak’s Multiple Comparison
35
Q

Research Statistics Final Review

Examples of Different Variances

A
  • A: No variance within groups, only between groups
  • B: Equal variance within groups; the groups are different
  • C: Greater variance within groups; the groups appear less different
  • D: Unequal variance within groups
36
Q

Research Statistics Final Review

Equal variances in independent groups designs = _ test ?

A

Equal variances in independent groups designs = Levene’s test

  • Tests the null hypothesis that “there is no difference in variance between groups”
  • Variance is the spread of the scores
  • Levene’s test p<.05 we reject the null hypothesis for equal variances
  • Variances are NOT equal
  • Levene’s test p>.05 we fail to reject the null hypothesis for equal variances
  • Variances are equal
37
Q

Research Statistics Final Review

When to Use (or Not Use) Odds Ratio = ?

A

When to Use (or Not Use) Odds Ratio

  • Used when we want to study risk OR used in case control studies
  • Classify participants by outcome
  • Odds of exposure by disease (yes/no)
  • Can be used in interventional studies to look at the odds improvement after treatment
38
Q

Research Statistics Final Review

When to Use (or Not Use) Relative Risk = ?

A

When to Use (or Not Use) Relative Risk

  • Used when we want to study risk RR is for cohort studies
  • You can study interventions using a cohort study design
  • We cannot use RR in case control because outcome has been determine and that is how we are grouping our participants
  • RR looks at “incidence”
  • Interventional studies can use OR
  • Outcome is known and used for grouping, so similar logic to case control/OR applies
39
Q

Research Statistics Final Review

Best Way to Remember When to Use RR/OR

  • Cohort Study = ?
  • Case Control = ?
A

Best Way to Remember When to Use RR/OR

  • Cohort Study = The “o’s” in cohort study are really close, kind of like family (i.e. relatives) = Relative Risk
  • Case Control = Here we have a, e and o’s. These are different and “at odds” with each other = Odds Ratio
40
Q

Research Statistics Final Review

RR/OR = 1 = ?

A

RR/OR = 1 = there is no risk increase or decrease

41
Q

Research Statistics Final Review

RR = 1.2 = ?

A

RR = 1.2, those with exposure are 1.2x more likely to develop the disease or exposed people are 20% more likely to develop the disease.

42
Q

Research Statistics Final Review

RR = 1.6 = ?

A

RR = 1.6, those with exposure are 1.6x (or 60% more likely) to develop the disease.

43
Q

Research Statistics Final Review

RR/OR = 1= ?

A

RR/OR = 1 = there is no risk increase or decrease.

44
Q

Research Statistics Final Review

OR = 1.2 = ?

A

OR = 1.2 = the odds of disease are 1.2 times higher (or 20% higher) in those with the exposure

45
Q

Research Statistics Final Review

OR = 1.6 = ?

A

OR = 1.6 = the odds of disease are 1.6x (or 60% more likely) in those with the exposure

46
Q

Research Statistics Final Review

I want to determine if there is a correlation between statistics grades (percentage) and the number of studies published after PT school. = ?

A

I want to determine if there is a correlation between statistics grades (percentage) and the number of studies published after PT school. = Pearson’s (Parametric)

47
Q

Research Statistics Final Review

I want to use a 5 point Likert scale to see if there is a correlation between attitudes about research and the number of research studies published after PT school = ?

A

I want to use a 5 point Likert scale to see if there is a correlation between attitudes about research and the number of research studies published after PT school = Spearman’s (Nonparametric)

48
Q

Research Statistics Final Review

  • Both variables are interval/ratio
  • Data meet assumptions

What test = ?

A
  • Both variables are interval/ratio
  • Data meet assumptions

What test = Pearson’s r

49
Q

Research Statistics Final Review

  • Both variables are interval/ratio
  • Data does NOT meet assumptions

What test = ?

A
  • Both variables are interval/ratio
  • Data does NOT meet assumptions

What test = Spearman’s rho (non-parametric)

50
Q

Research Statistics Final Review

  • One or both variables are ordinal

What test = ?

A
  • One or both variables are ordinal

What test = Spearman’s rho (non parametric)

51
Q

Research Statistics Final Review

  • Both variables are nominal
  • Measuring risk, yes
  • Classified by exposure

What test = ?

A
  • Both variables are nominal
  • Measuring risk, yes
  • Classified by exposure

What test = relative risk

52
Q

Research Statistics Final Review

  • Both variables are nominal
  • Measuring risk, yes
  • Classified by outcome

What test = ?

A
  • Both variables are nominal
  • Measuring risk, yes
  • Classified by outcome

What test = Odds Ratio

53
Q

Research Statistics Final Review

  • Both variables are nominal
  • Measuring risk, yes
  • Classified by outcome

What test = ?

A
  • Both variables are nominal
  • Measuring risk, yes
  • Classified by outcome

What test = Odds Ratio

54
Q

Research Statistics Final Review

  • Both variables are nominal
  • Measuring risk, no
  • Classified by outcome

What test = ?

A
  • Both variables are nominal
  • Measuring risk, no
  • Data meet assumptions, yes

What test = Chi Square

55
Q

Research Statistics Final Review

ICC Models

  • Model 1 = ?
  • Model 2 = ?
  • Model 3 = ?
A

ICC Models:

Model 1

  • Raters are chosen from a larger population; some subjects are assessed by different raters (rarely used)

Model 2

  • Each subject assessed by the same set of raters, and we want to generalize to other raters. Used for test-retest and inter-rater reliability.

Model 3

  • Each subject is assessed by the same set of raters, but the raters represent the only raters of interest.
  • Used for intra-rater reliability or inter-rater when you do not wish to generalize the scores to other raters.

DPT 673 - Research Statistics (3 decks)

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