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LECOM Biostatistics

LECOM Biostatistics Freeman

Seven Core Competencies OPP, Pt Care, Medical Knowledge, Practice-Based Learning and improvement, Interpersonal and Communication Skills, Professionalism, Systems-based Practice
Quantitative each value is a number that represents an amount or count *interval/ratio
Qualitative each value is a word or code that represents a class or category *nominal/ordinal
Mean sum of all observations divided by N (number of total observations)
This MCT is most sensitive to outliers Mean
Median middle value when observations (ordinal) are ranked in order
Use this MCT when data is skewed Median
Mode value most frequently observed
When can only the Mode be used with nominal data
Find variance by square individual deviation scores then average them
Standard Deviation in relation to the variance Square root of the variance
The normal curve is symmetrical and has mean=median=mode
Skewedness is named + or – based on where the outlier is
Kurtosis describes the peakness or flatness of a curve
Leptokurtic curve is thin & peaked
Platykurtic curve is flat and wide
Causality must be determined because statistical correlation does not always mean causation
r=correlation coeff. Which ranges from -1 to 1
Positive or negative reflects slope of the line
The closer to 1 the coeff. Is the more correlated the data is
R*2 (squared) shows amount of variation in the dependent variable explained by the independent variable
Total number of cases of disease or injury in a population at a particular point in time or during a specific time period prevalence
Measure of NEW cases in a population over a specific time period incidence
Those who have the disease and tested positive divided by the total number of those who have the disease sensitivity
The ability of a test to correctly identify those who do not have a disease specificity
Probability that the person tests negative if they do not have the disease specificity
Probability that a person will test positive if they have the disease sensitivity
Likelihood that a positive test is predictive of having the disease PPV
PPV = True positives divided by sum of all positive tests
Likelihood that a negative test is predictive of being disease free NPV
Likelihood Ratio of Positive test means how much more likely is an infected Pt to test + than a disease free Pt
Likelihood Ratio of Positive test calculation Sensitivity/(1-Specificity)
Likelihood Ratio of Negative test means how much more likely is a disease free person to test – than an infected Pt
Likelihood Ratio of Negative test calculation (1-sensitivity)/Specificity
CER Control Event Rate
EER Experimental Event Rate
AAR Absolute Risk Reduction
RRR Relative Risk Reduction
Number Needed to treat means number you have to treat to “save” one
NNT = 1/AAR (negative value)
Number Needed to Harm means number of patients you need to treat to have one with adverse effects
NNH for control and experiment = 1/ AAR (positive value)
Hypothesis testing step 1/6 State the question
Hypothesis testing step 2/6 Formulate Null and Alternative hypothesis
Hypothesis testing step 3/6 Establish a decision rule
Hypothesis testing step 4/6 Do the research
Hypothesis testing step 5/6 make a decision
Hypothesis testing step 6/6 Interpret
Decision rule uses p which means what probability of being wrong are we willing to tolerate
Decision rule using p=0.05 means if p<0.05 reject the null hypothesis
Type I error (alpha) means Determined the treatment works but it actually doesn’t
Type II error (beta) means Determined the treatment didn’t work when it really does
Power refers to a test’s ability to find a difference if one really exits
Power = 1-beta
z-statistic can only be used with a NORMAL CURVE ie ideal case
If 1/(EER-CER) > 0 than it is the Number Needed to Harm
If 1/(EER-CER) <0 than it is the Number needed to Treat
Created by: csheck