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NSG 324 (mcp) > Chapter 14: Quantitative Data-Statistical Analysis > Flashcards

Chapter 14: Quantitative Data-Statistical Analysis Flashcards

1
Q

Things to keep in mind for this LOOOOONG chapter:

A

1- you will not be asked to calculate any of the parameters described

2- Research studies are not published and peer-reviewed if they used the wrong type of statistical test or measure to analyze their study.

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2
Q

Quantitative Studies:

Levels of Measurement (5):

A

1) Nominal
2) Ordinal
3) Interval
4) Ratio
5) Continuous variable

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3
Q

Quantitative Studies: Levels of Measurement
_______ measurements are two values that can be accurately described by their ratio; the highest level, and the numbers included are able to have a meaningful zero.

Give an example:

A

Ratio

Example: Weight
A 200-pound person is clearly twice the weight of a 100-pound person.

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4
Q

Quantitative Studies: Levels of Measurement
______ measurements rank people on attributes with a number that clearly specifies a distance between the two.

Give an example:

A

Interval

Example:
An IQ test

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5
Q

Quantitative Studies: Levels of Measurement
_______ measurements rank people based on an attribute, such as ADLs.

Give an example:

A

Ordinal

Example: ADL measurements
4 = being independent
1 = being completely dependent
The number relates to the rating of an attribute.

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6
Q

Quantitative Studies: Levels of Measurement

_________ are variables with interval and ratio measurements.

A

Continuous variables

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7
Q

Quantitative Studies: Levels of Measurement
_______ measurement is the lowest level and involves using numbers to designate attributes. In other words, things are indicated by a numeric value, but that numeric value can’t be used mathematically.

Give an example:

A

nominal

Example: Eye color
Brown can be 1
Blue can be 2
Green can be 3, etc.

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8
Q

Quantitative Studies:
_________ Statistics are used to synthesize and describe data.
________ are calculated values such as averages and percentages.
_______ is a descriptive index from a sample.

A

Descriptive statistics

Parameters

Statistic

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9
Q

Quantitative Studies: Descriptive Statistics

Name the 4 Types of Descriptive Statistics

A

1) Frequency distribution
2) Symmetric distribution
3) Skewed distribution
4) Normal distribution

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10
Q

Quantitative Studies: Descriptive Statistics
A ______ distribution is a bell-shaped curve that has a lower peak than other types of distributions.
SD within 1?
SD within 2?

A

normal

For a normal distribution or bell-shaped curve,
68% of values will be within 1 SD of the mean.
95% of values will be within 2 SD of the mean.

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11
Q

Quantitative Studies: Descriptive Statistics

________ distributions are ones where if the graph is folded in half the two halves would be superimposed.

A

Symmetric

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12
Q

Quantitative Studies: Descriptive Statistics

In a _______ distribution, the majority of the data peaks to one side.

A

skewed

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13
Q

Quantitative Studies: Descriptive Statistics
A _______ distribution takes a list of values and organizes it lowest to highest and includes a count.

Give an example:

A

frequency

Example:
If there were 10 values and 5 of them were 80, it would list 80 once and put a count of 5 and a percentage of 50%.

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14
Q

Quantitative Studies:
______ ________ includes methods to determine a central value for a set of numbers.

This includes _____, _____, and ______.

A

Central tendency

Mode, Median, and Mean

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15
Q

Quantitative Studies: Central Tendency

The ____ is the number that occurs most frequently in a distribution.

A

mode

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16
Q

Quantitative Studies: Central Tendency

The ______ is the point in a distribution that divides scores in half.

A

median

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17
Q

Quantitative Studies: Central Tendency

The _____ equals the sum of all values divided by the number of participants.

A

mean

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18
Q

Quantitative Studies: Central Tendency
Measures of central tendency can be the same for two different sets of distributions.
This is known as _______.

A

variability

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19
Q

Quantitative Studies: Variability

The _____ is the highest minus the lowest score in a distribution.

A

range

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20
Q

Quantitative Studies: Variability
The ___________ is a variability index calculated based on every value in a distribution; it is the average amount of deviation of values from the _____.

A

standard deviation

average amount of deviation of values from the MEAN

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21
Q

Quantitative Studies: Variability + Standard Deviation

The lower the standard deviation, the more _________ the distribution.

A

homogenous

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22
Q

What Human attributes occur as bell-shaped curves?

A

height and intelligence

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23
Q

Quantitative Studies: Bivariate Descriptive Statistics

If a frequency distribution is based on two variables instead of one, a _____________ can be used to depict the data.

A 
crosstabs crosstable (Crosstabulations)
-Two-variable descriptive statistics

Correlation
Correlation coefficient

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24
Q

Quantitative Studies: Bivariate Descriptive Statistics

Crosstabulations are used for what 2 kinds of data?

A

Used with nominal or ordinal data

The most widely used correlation statistic is Pearson’s r (the product-moment correlation coefficient).

Spearman’s rho is a correlation coefficient calculated for values on an ordinal scale.

A correlation matrix displays correlation coefficients in tables displaying rows and columns.

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25
Q

Quantitative Studies: Bivariate Descriptive Statistics

_________ are methods to describe relationships between two variables, and utilizes the ________ _________, which is the intensity and direction of the relationship between two variables.

A

Correlations

correlation coefficient

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26
Q

Quantitative Studies: Bivariate Descriptive Statistics

Correlation coefficients range from _________.

A

range from -1.0 to 0 to 1.0.

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27
Q

Quantitative Studies: Bivariate Descriptive Statistics + Correlation coefficients:
A +1.0 would mean a _______ relationship.

Values b/t 0 and +1.0 represent a _____relationship.

Values b/t -1 and 0 represent a ______ relationship

A

Perfect relationship

Positive relationship

Negative relationship

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28
Q

Quantitative Studies: Bivariate Descriptive Statistics
Name the 2 Types of Correlation Coefficients:

Which one is the most widely used correlation statistic?

A

1) Pearson’s r –> MOST WIDELY USED

2) Spearman’s rho

29
Q

Quantitative Studies: Bivariate Descriptive Statistics + Correlation Coefficients:
The product-moment correlation coefficient =

A

Pearson’s r –> MOST WIDELY USED

Spearman’s rho is a correlation coefficient calculated for values on an ordinal scale.

30
Q

Quantitative Studies: Bivariate Descriptive Statistics + Correlation Coefficients:
________ is a correlation coefficient calculated for values on an ordinal scale.

A

Spearman’s rho

31
Q

Quantitative Studies: Bivariate Descriptive Statistics + Correlation Coefficients:
What is used to display correlation coefficients in a table with rows and columns?

A

A correlation matrix displays correlation coefficients in tables displaying rows and columns.

32
Q

Quantitative Studies: Describing Risk

________ risk is the proportion of people who experienced an undesirable outcome in each group.

How do we calculate this and what is it called?

Give an example:

A

Absolute risk

Absolute risk reduction is a comparison of the two risks.

Example:
one group of people had education on falls and are the experimental group, and the control group did not have education on falls.
10% of individuals in the experimental group had falls, while 30% of the individuals had falls in the control group.
Experimental group AR = 0.10
Control group AR = 0.30

Calculation:
(Experimental group AR) - (Control group AR) x100 =
.30 - .10 = .20 or 20%.
This suggests that 20% more of the control group would not have fallen with the intervention.

33
Q

Quantitative Studies: Describing Risk
_________ is the ratio of two odds, and gives us the odds of an undesirable effect.

How do we calculate this?

Give an example:

A

Odds ratio

Calculation:
(# who didn’t fall) / (# who did fall) = odds ratio

Example:
10% of individuals in the experimental group had falls, while 30% of the individuals had falls in the control group.

For the experimental group,
70 / 30 = 2.33
For the control group,
90 / 10 = 9.00

Odds ratio = 2.33 / 9 = 0.259
This means the odds of falling with education is 25%, and the odds of falling without education is 400% more likely.

34
Q

Quantitative Studies: Describing Risk
The number needed to treat estimates is ……?

How we calculate this?

Give an Example:

A

how many people need to receive an intervention to prevent one undesirable outcome

Calculation:
1 / Absolute risk reduction

Example:
1 / .20 = 5
Five people would need to receive education on falls.

35
Q

Quantitative Studies:
________ statistics use the law of probability to test research hypotheses with data.

Use ____ to test research hypotheses.

A

Inferential statistics

Use data to test research hypotheses.

36
Q

Quantitative Studies: Inferential Statistics
A confidence interval relates to the probability of being right. A confidence interval of __%-__% is the goal for most researchers.

A

confidence interval of 95%-99%

GOAL FOR US:
To understand that in a research study, seeing the researchers describe obtaining a confidence interval of 95% or 99% indicates a high probability of the data being right.

37
Q

Quantitative Studies: Inferential Statistics
______ ______ of the Mean is the standard deviation of the mean of a sample.

The higher the number –> ?

What sample size (small or large) will help reduce the chance of outlying data?

A

Standard Error of the Mean (SEM)

The higher the number –> the more error associated with the sample selected.
- In other words, a lower SEM reflects a more appropriate sample size.

LAAAAARGE

38
Q

Quantitative Studies: Hypothesis Testing

Hypothesis testing uses ______ criteria to determine if the hypothesis is supported or rejected.

A

uses objective criteria

39
Q

Quantitative Studies: Hypothesis Testing
______ ________ means the results are not likely to be due to chance.

What Standard Deviation value indicates this?
What Confidence Interval (%) indicates this?

A

Statistical significance

Falls within 2 standard deviations of the mean

Confidence intervals of 95% or greater represent statistically significant values.

40
Q

Quantitative Studies: Hypothesis Testing

A _______ result means that the results could be due to chance.

A

nonsignificant

41
Q

Quantitative Studies: Hypothesis Testing

A ____ hypothesis is when there is no relationship between the independent variable and dependent variable.

A

null hypothesis

42
Q

Quantitative Studies: Hypothesis Testing
A type __ error is rejecting the null hypothesis that is in fact true.

Type __ error assumes the null hypothesis is true when in fact the independent variable did have an effect.

A

Type I

Type II

43
Q

Quantitative Studies: Hypothesis Testing

A power analysis is calculated to determine the chance of a type __ error.

A

Type II = power analysis

44
Q

Quantitative Studies: Hypothesis Testing

Alpha, or level of significance, is calculated to determine the chance of a type __ error.

A

Type I error = alpha

45
Q

Quantitative Studies: Hypothesis Testing

Is it possible to eliminate Type I and Type II errors?

A

No, IMPOSSIBLE to eliminate type I and type II errors

So, statistical tests will aim to be statistically significant.

46
Q

Quantitative Studies: Specific Statistical Tests
Name the 3 Specific Statistical Tests:

What value determines Statistical significance for all 3 tests?

A

1) T-tests
2) Analysis of Variance (ANOVA) test
3) Chi-Squared Test (X^2)

A p value of <0.05 indicates Clinical Significance

47
Q

Quantitative Studies: Specific Statistical Tests

T-tests, ANOVA tests, and Chi-squared tests use _____ to determine Clinical Significance.

A

p value

<0.05 = Clinical Significance

48
Q

Quantitative Studies: Specific Statistical Tests
_________ is used to test mean group differences of three or more groups.

Calculates a __ value, which varies for each study.

A

Analysis of variance (ANOVA) test

ANOVA calculates a F value

49
Q

Quantitative Studies: Specific Statistical Tests
A parametric test for testing differences in two group means is called a _______.

Calculates a __ value, but the individual value is not important.

A

T-test

Calculates a t value, but the individual value is not important.

50
Q

Quantitative Studies: T-test
_______ t-test is appropriate for two different groups of people.
_______ t-test is used when one group is tested at two different points in time.

A

Independent t-test

Paired t-test

51
Q

Quantitative Studies: Specific Statistical Tests
A _______ test focuses on the difference in proportion.

Calculates the value of ______, which varies from test to test.

Give an example:

A

chi-squared test

Calculate the value of chi-squared, which varies from test to test.

If blood sugars were controlled in 60% of patients with a diabetes educational intervention, versus 40% of patients without, is the 20% real?

52
Q

Quantitative Studies: Multivariate Statistical Analysis

Name the 3 Types of Multivariate Statistical Analysis Tests:

A

1) Multiple Regression
2) Analysis of Covariance (ANCOVA)
3) Logistic Regression

53
Q

Quantitative Studies: Multivariate Statistical Analysis
_________ is a combination of ANOVA and multiple regression.

This test is good when there is not control through _______.

ANCOVA attempts to control _________.

A

Analysis of Covariance (ANCOVA)

ANCOVA is good when there is not control through randomization.

ANCOVA attempts to control covariates of confounding variables.

54
Q

Quantitative Studies: Multivariate Statistical Analysis
___________ measures several independent variables, called ______ variables in this type of test.

A statistic called a _____________ is calculated and known as R.

A

Multiple Regression

Predictor variables

multiple correlation coefficient (R)

55
Q

Quantitative Studies: Multivariate Statistical Analysis
___________ measures several independent variables, called ______ variables in this type of test.

A statistic called a _____________ is calculated and known as R. R varies from _________.

A

Multiple Regression

Predictor variables

multiple correlation coefficient (R)

R varies from 0.0 to 1.00.

56
Q

Quantitative Studies: Multiple Regression
________ gives a % of how influential the predictor variables were.

A higher R-squared value means –> ?

A

R-squared

A higher R-squared value means –> it is more likely the predictor variables accounted for the variation.

57
Q

Quantitative Studies: Reliability Measurements
What are the 3 Types of Reliability Tests?

Indicate what each test calculates:

For all of these, scores closer to ___ means a higher level of reliability.

A

1) Test-Retest Reliability
- Intraclass correlation coefficient (ICC)

2) Interrater reliability
- Cohen’s kappa

3) Internal consistency reliability
- Coefficient alpha or Cronbach’s alpha

For all of these, scores closer to 1.0 means a higher level of reliability.

58
Q 
Quantitative Studies: Reliability Measurements
Intraclass correlation coefficient is used for \_\_\_\_\_\_\_ reliability and ranges from 0.00 to 1.00.
A

test-retest reliability

59
Q

Quantitative Studies: Reliability Measurements
Cohen’s kappa is used for dichotomous classifications and is used for _______ reliability; helpful to determine if two individuals would rate something similarly.

A

Interrater reliability

60
Q

Quantitative Studies: Reliability Measurements
Coefficient alpha aka Cronbach’s alpha is used for __________ reliability, which measures how often components of a multi-component tool measure the same attribute

A

Internal consistency reliability

61
Q

Quantitative Studies: Validity Assessment

Name the 3 Types of Validity

A

1) Content Validity
2) Criterion Validity
3) Construct Validity

62
Q

Quantitative Studies: Validity Assessment
_____ validity determines if the content of the items adequately reflects the construct of interest.

An index of ___ or higher indicates good validity.

A

Content Validity
- Experts meet to rate each item to determine a content validity index.

An index of 0.90 or higher indicates good content validity.

63
Q

Quantitative Studies: Validity Assessment
______ validity concerns the extent to which a measure is truly measuring the target construct. It uses various procedures such as Pearson’s r value, or an independent group t-test.

A

Construct validity

64
Q

Quantitative Studies: Validity Assessment
______ validity concerns the extent to which scores on a measure are consistent with a gold standard criterion.

Two terms fall under this type of validity, What are they?

A

Criterion validity

1) Sensitivity
2) Specificity

65
Q

Quantitative Studies: Criterion Validity Assessment

________ is the ability of a measure to correctly screen or diagnose a condition.

A

Sensitivity

Think: SENSITIVITY = HOW MANY TIMES DID I GET CLOSE TO THE TARGET

the ability of a test to correctly identify patients WITH a disease.

66
Q

Quantitative Studies: Criterion Validity Assessment

________ is the measure’s ability to correctly identify non-cases or screen out those without the condition.

A

Specificity

Think: SPECIFICITY = HOW CLOSE TO A TARGET

the ability of a test to correctly identify people WITHOUT the disease

67
Q

Quantitative Studies: Criterion Validity
Sensitivity vs Specificity using Walter’s Example of a flu swab diagnostic test:

A specific flu swab would….

A sensitive flu swab would…

A

A specific flu swab would NOT be positive for strep or other conditions.

A sensitive flu swab would be positive for the flu MOST of the time.

68
Q

Quantitative Studies: Criterion Validity
Sensitivity vs Specificity using Walter’s Example of a flu swab diagnostic test:
What if a flu swab always caught the flu, but also would show positive for strep?

A

highly sensitive, but has LOW specificity

69
Q

Quantitative Studies: Criterion Validity
Sensitivity vs Specificity using Walter’s Example of a flu swab diagnostic test:
What if a flu swab ONLY detected the flu, but only detected half the cases of flu successfully?

A

highly specific, but has LOW sensitivity

NSG 324 (mcp) (21 decks)

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