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PUB561 > Module 3 > Flashcards

Module 3 Flashcards

1
Q

How do you summarise categorical data?

A
  • frequencies, proportions or percentages
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2
Q

What test is used to compare the distribution of categorical variable to the hypothesised distribution?

A

chi squared goodness-of-fit test /one sample chi squared test

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3
Q

What is an example of a one-sample chi squared test hypothesis?

A

H0: is evenly distributed
H1: is not evenly distributed

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4
Q

Why is the one sample chi-squared test (chi squared goodness-of-fit test) used?

A
  • to quantify the discrepancy between the expected and observed frequencies
    e. g. between sample and hypothesised value
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5
Q

What is the shape of the chi-squared distribution?

A
  • non-symmetric (always positive)

- changes with the df (degrees of freedom)

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6
Q

What is degree of freedom?

A

= number of groups -1

- indicates how many of the data points are ‘flexible’

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7
Q

What test is used to look at association between 2 categorical variables?

A
  • chi-squared test of independence
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8
Q

How is the test statistic calculated for chi-squared test of independence?

A
  • same as normal except need to calculate for each cell in the table
    e. g. (column total x row total)/overall total
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9
Q

How do you calculate the df for a contingency table/cross-table?

A

df = (number of rows - 1) x (number of columns - 1)

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10
Q

What does a small x^2 value mean?

A
  • when the observed value is approximately eyqla o the expected value in each cell
  • only vary due to sample variability
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11
Q

What causes a large x^2 value?

A
  • sample variability (given by p-value)

- Null hypothesis is not true

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12
Q

What are the chi-squared test of independence assumptions?

A
  • the observational units are independent

- the expected cell counts should be >5

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13
Q

What are the limitations of x^2 test of independence?

A
  • not informative about how variables are related

- only really be used for bivariate analysis

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14
Q

What are other options for assessing associations in categorical variables?

A
  • relative risk

- odds ratio

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15
Q

Can chi-squared test of independence be used for before and after?

A
  • no because the measurement is on the same individual
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16
Q

What is a McNemar’s test?

A
  • used for 2x2 tables to test repeated measurments on the same variable

SIMPLE CONCEPT:

  • if no change, participants stay on diagnoal
  • if change, participants move off the diagonal
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17
Q

What test is used for continuous data?

A

one sample t-test

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18
Q

What is a t-test?

A
  • parametric test used for testing differences in means

- tests the hypothesis that the means of a sample is equal to a fixed value

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19
Q

What does the one sample t-test assume?

A
  • data is normal distributed
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20
Q

What is the test statistic equation for a one-sample t-test?

A

t = (sample mean - expected value)/ (sample sd/ square root of the sample size)

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21
Q

what influence the fatness of the t-test distribution tail?

A
  • degrees of freedom
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22
Q

What makes a t-distribution more normally distributed?

A
  • bigger sample size/more df
23
Q

What is the t-test distribution if n>30?

A
  • sampling distribution of means is approximately normally distributed
24
Q

When is a two sample/independent sample t-test used?

A

compare two groups

  • dependent is continuous
  • independent is categorical
25
Q

What are the assumptions for a two-sample t-test?

A
  • distribution is normally distributed or >30
  • results come from two independent samples
  • variances in the two groups are the same
26
Q

what test is used if it is unknown if the sample is normal?

A

non-parametric test (mann-whitney test)

27
Q

What does a mann-whitney test/Wilcoxon Rank sum test compare?

A
  • medians of two samples
28
Q

When is a paired t-test used?

A
  • before and after

- left and right arm

29
Q

What is a ANOVA t-test?

A
  • one way analysis of variance

- used when >2 groups

30
Q

What is the ANOVA hypotheses?

A 
Null = means are the same
H1 = at least one mean differs
31
Q

What are the two types of variation within data for ANOVA?

A
  • between groups

- within group

32
Q

How can you tell if the variation is between groups?

A
  • distributions are at different levels of the x-axis
33
Q

How can you tell if the variation is within groups?

A
  • the distributions overlap but are very wide
34
Q

How do you calculate total variation?

A

sstotal (sum of squares) = sum of (mean - overall mean)^2

35
Q

What does the conversation of SS to MS (mean square) for?

A
  • account for different df in each calculation
36
Q

What is the total variance equation?

A

MStotal = SStotal/(N-1)

37
Q

What is the between group variance equation?

A

MSgroups = SSgroups/(k-1)

38
Q

What is the within group variance equation?

A

MSerror = SSerror/(N-k)

39
Q

What does the ratio of MSgroups/MSerror show?

A
  • how much bigger groups effect is compared to random noise
40
Q

What is the variance ratio?

A
  • ratio of two variances

- denoted F (f is the test statistic for ANOVA)

41
Q

When is a post-hoc test used?

A
  • if the H0 is rejected in an ANOVA to determine which means are different
42
Q

What is the most common post hoc test?

A
  • tukey
43
Q

What is the steps for interpreting ANOVA results?

A
  • check ANOVA assumptions
  • conduct ANOVA
  • if p-value>0.5 then do not reject H0)
  • if p-value<0.5 then reject and do post-hoc testing
44
Q

What test is used for normality assumption (ANOVA)?

A
  • non-parametric test such as kruskal-wallis test
45
Q

What test is used for equal variances assumption?

A
  • levene’s test to test the H0 that variances of groups is the same
  • if test is significant the variances are not equal
46
Q

what test statistics equation is used for one-sample chi squared test?

A

= observed - expected/precision

47
Q

What type of test is a t-test?

A
  • parametric test
48
Q

What is an assumption of a parametric test?

A
  • assumes the data follows a known distribution
49
Q

What does a one-sample t-test test?

A
  • the hypothesis that the mean of a sample is equal to a fixed value
50
Q

What t-test is used to decide if variances are equal?

A

Levene’s test

51
Q

What is an advantage of paired test?

A
  • takes out the variation between patients and only the effect of a drug
52
Q

What are the assumptions for ANOVA?

A
  • normally distributed or >30
  • equal variances
  • independence among observations
53
Q

What number of type 1 error is achieved after all post-hoc tests?

A
  • 0.05

PUB561 (3 decks)

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