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Occupational Health > Statistics > Flashcards

Statistics Flashcards

0
Q

Nominal data

A

In category, non-parametric

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1
Q

Study Power?

A

The power of a study is the probability of detecting a significant difference between treatments or study groups when there really is one.
Low power increases the likelihood of failing to identify a statistically significant difference when a real difference does exist.
High power (80% or more) is desirable .
Power is affected by sample size, etc.

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2
Q

Ordinal data?

A

In order, with unequal interval,non-parametric

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3
Q

Interval data?

A

Equal interval
No absolute zero
Cannot compute ratio
parametric

Eg Tm in Celsius or Fahrenheit

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4
Q

Ratio data?

A

Equal interval
with absolute zero or true zero
Can calculate ratio
parametric

Eg. Wt, hight, Kelvin Tm

“NOIR”

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5
Q

Measurement of central tendency?

A

Mean
Median
Mode

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6
Q

Mean= Median = Mode, what distribution?

A

Normal distribution

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7
Q

Relationship of mean, median and mode in right (positive) distribution?

A

Right skewed -Tail on the right
Mean>Median>mode

(Rule of thumb: mean always follows the tail)

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8
Q

The relationship of mean, median and mode in left skewed distribution?

A

Tail is on the left of the distribution

Mean<Mode

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9
Q

For normal distribution, select statistic method?

A

Select Parametric statistics test

Eg. Student t-test, chi-square, ANOVA, ANCOVA, regression analysis

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10
Q

For non-normal distribution, eg. Bimodal, skewed, etc. test methods selection?

A

Non-parametric test eg.Fisher’s exact test, McNemar test,Mann-Whitney U test, Wilcoxon’s rank sum test, Kruskall-wallis test

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11
Q

Ways of obtaining random sample?

A
  1. Simple random sampling
  2. Systemic random sampling
  3. Stratified random sampling
  4. Cluster sampling
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12
Q

Bias?

A

Systemic error

Impacts internal validity

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13
Q

Chance

A

Radom

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14
Q

Confounder?

A

Associated with exposure (risk) and outcome
An independent risk factor for the outcome
Not in the causal pathway between the risk factor and disease

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15
Q

Power

A

The chance of finding an effect in your sample if it truly exist in the population.

Power is not a question in a study that shows a significant effects.

If a study results had failed to show a significant difference (p>0.05) between the two groups, one may wonder whether the study had sufficient power.

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16
Q

When apply to a population,
Given sensitivity and prevalence,
True positive =?
False negative =?

A

True Positive = Sensitivity x Prevalence

False negative = (1- Sensitivity) x Prevalence

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17
Q

When apply to a population, given Specificity and Prevalence,
True negative =?
False positive =?

A

True Negative = Specificity x (1- Prevalence)

False positive = (1- Specificity) x (1-Prevalence)

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18
Q

Regression toward the mean

A

In any group selected on a characteristic with substantial day-to-day variation, many will have values closer to the population mean when the measurement is repeated and worst pts will improve.

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19
Q

Baseline drift

A

Which occurs with measurement on certain machines that requires frequent calibration.

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20
Q

Hawthorne effect

A

A tendency among study subjects to change simply because they are being studied or watched.

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21
Q

1SD =? %
2SD =? %
3SD =? %

A

1 SD = 68% (Z score = 1)
2 SD = 95% (Z score = 2)
3 SD = 99% (Z score = 3)

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22
Q

When two events are independent, the probability of either will occur?

A

Is the sum of their probability, minus the probability that both will occur.
P (A or B) = P (A) + P (B) - P (A and B)

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23
Q

When two conditions are mutually exclusive, the probability that either one will occur is

A

The sum of their probability

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24
Randomization
Assignment occurs by chance
25
ROC curve - Receiver-operator curve
X axis: 1 - specificity, or the false - positive rate Y axis: Sensitivity
26
ROC curve is used to determine
Optimal Cut-off point for the respective test. In general, the point closest to the upper-left corner, where sensitivity is highest and the false-positive rate is lowest, is chosen as the cut-off.
27
In ROC cure, the Area Under the Curve (AUC) is used to?
To calculate the diagnostic accuracy (best sensitivity and specificity) of the test, that is the probability of correctly identifying disease based on the result of the test. The larger the area under the curve, the better the test.
28
Kappa statistic
Used for reliability studies, eg to assess inter-rater reliability or intra-eater reliability. Used in assessing the degree to which two or more raters, examine the same data, agree when it comes to assigning the data to categories.
29
Effect modification
Occurs when one factor modifies the effect on outcome of another.
30
Confounder
Occurs when the association between two variables is distorted by the fact that both are associated with a third. Eg. The association between coffee and lung cancer is distorted by smoking
31
CV (coefficient of variation)
CV = SD/X x 100% 1. Used for compare the relative spread of data for 2 variables (eg. Height and weight) 2. Used to evaluate precision of the measurement of a single variable (x-ray film reading by two physicians)
32
Histogram
For continuous variables
33
Bar graph
For categorical data
34
Scatter plot
For association
35
Types of random samples
Simple random Systematic random Stratified random Cluster random
36
Simple random sampling
Every unit in the population had the same probability of being selected, chance alone determines whether a particular unit in the population is selected for the sample
37
Systematic random sampling
Every k th member is selected from the population
38
Stratified random sampling
- Population is divided into heterogeneous groups (strata) (eg. black, white, Hispanic, Asia) and a random sample is taken from within each group - Ensures equal numbers of each strata in final sample.
39
Cluster random sampling
Population is divided into homogenous group (cluster) and a random sample of these groups is taken. eg a school, a community, etc
40
Z score
Z = (X - U)/sigma Any normal distribution can be transformed to the standard normal to get a Z score for a given value X
41
Wilcoxon's signed rank test is an non-parametric equivalent of ?
Paired t-test
42
One sample t-test
To compare the sample mean with the mean of the population
43
Two samples t-test
To compare the mean of two groups
44
Paired t-test
To compare the mean of before and after
45
ANOVA
Used for more than two groups
46
Chi-square test
Compare two proportions
47
Fisher's exact test
Is used if expected count on a cell is less than 5
48
NcNemar's chi-square test
For paired proportions
49
Spearman's rank correlation coefficient is a non-parametric equivalent to ?
Pearson's correction coefficient
50
Coefficient of determination
% of variation in Y explained by X
51
Simple linear regression
Dependent variable is continuous | One independent variable
52
Multiple linear regression
Dependent variable is continuous | More than one independent variables
53
Logistic regression
Dependent variable is dichotomous | OR is used for estimation
54
Survival analysis
Time to the event | Hazard rate is use for estimation
55
Collinearity
Collinearity is a linear relationship between two explanatory variables. Collinearity can result in unstable beta coefficient estimates.
56
Funnel plot
A graph designed to check for the existence of publication bias in systematic reviews and meta-analyses
57
When can Poisson distribution be used as a good approximation of a binomial distribution?
In general, p should be small , 15
58
Type 1 error | Or alpha
Reject H0 when it is true.
59
Type 2 error | Or beta
Accept H0 when it is actually false.
60
For Paired data (pre and post, paired), what test to choose?
For parametric data, using - Paired t test ( pre and post, paired), For non-parametric data, using -Wilcoxon's signed rank test
61
To compare 2 group means, what test to choose?
For parametric data, using - Student t test For non-parametric data, using -Wilcoxon's rank sum test (also termed Mann-Whitney U test.
62
To compare to proportions, what test to choose?
For parametric data, using - Chi-square For non-parametric data, using - Fisher exact probability test - used when at least 1 cell in a contingency table has an expected count s Chi-square test for paired proportion.
63
More than two groups, what test to choose?
For parametric data, using - ANOVA For non-parametric data, using - Kruskal-Wallis test
64
For correlation, what test to choose?
For parametric data, using - Pearson's correlation For non-parametric data, using - Spearman's correlation Multiple regression - more than one independent variable s
65
Time to event analysis
1. Kaplan-Meier analysis 2. Cox proportional Hazard Regression - a combination of multiple logistic regression techniques with survival methods
66
Dependent variants categorical (binary, eg. Cured vs not cured), what test to choose?
Logistic regression
67
SD
How scattered the data is.
68
SEM
Precision of the mean. | How precise the data is.

Occupational Health (69 decks)

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