Exam 1 Flashcards
Nominal
Qualitative or categorical
Examples: Ethnicity, race and gender
Nominal in medicine
categorical variable with only two categories
Example: Outcomes of medical treatment or surgical procedure: succesful/not
Ordinal
ranks-order cases in terms of quantity of a particular characteristic.
Examples: 1st, 2nd, 3rd….
Ordinal Scales in Medicine
Determines a patients amount of risk or the appropriate type of therapy.
Percentages and proportions are often used
Numerical Scales
Continuous-quantitative, interval, dimensional
Examples: height, weight, IQ, Age
Numerical Scales-Discrete
A variable in which possible scores have limited values.
Examples: Numbers of brothers, sisters, operations, and bone fractures
Descriptive Statistics
Central tendency gives us an idea of the typical value of a distribution
Measures of the middle -center of distribution
Dispersion (or Variabiliity)
tells us how different the data is from eachother, how spread out it is
Inferential Statistics
tells us if the difference we see is likely caused by chance (if real or not)
if descriptive statistics are probably accurate
if sample represents population
Variance
A variable that causes variance: experimentation or observation
Mean
a measure of central tendency
Average, Xbar
mode
a measure of central tendency.
the value occurs frequently
median
a measure of central tendency
the middle observation or the point at which half the observations are smaller and half are larger
A score at 10th percentile is
higher than 10% of all scores
A score at 75th percentile is
higher than 75% of all scores
The median is the score at
the 50th percentile
mean > median
positively skewed
mean < median
negatively skewed
Standard Deviation
used to measure dispersion with medical and health data
average of the spread of the observations around the mean
average distance of scores from their own mean
Variance (mean square)
the mean of the squared deviations
Correlation Coefficient
How strong is the relationship between two continuous variables?
if slope of SD line is positive
R is positive
Postive Correlation
always lie between 0 and 1
if r is close to 1=strong relationship
Negative correlation
Always lie between -1 and 1=if SD line goes down and r<0
if r=-1, perfect negative relationship
Randomized Control Trials
measures primary outcome of randomly assigned participants
participants have an equal likelihood of being assigned to intervention
strongest study desgin
required for FDA and NDA
In RCT
blinding is important
Validitty
the extent to which an instrument measures what it is intended to measure
degree to which findings are correct
Internal Validity
The outcome of interest (dependent variable) caused by the treatment (independent variable)
How to strengthen internal validity?
include a control group
random assignment-equally distributed across groups
why is internal validity important?
establishes cause and effect relationship
strong evidence of causality
low degrees of internal validity=little or no evidence of causality