FANDOM



TYPE OF ERRORS

  • Your Hypothesis: difference exists between A and B
  • Null Hypothesis: (Contradicts your Hypothesis) there is no difference between A and B


Type I Error: Incorrectly rejecting the null hypothesis

  • (The study showed that there is difference but in fact there is not difference, you think your study was successful but in fact it wasn’t!)
  • Type I Error = False Positive
  • p-value: chance of making type I error
  • (p<0.05 = <5% chance of commenting this error)


Type II Error: Incorrectly accepting the null hypothesis

  • (The study showed that there is no difference but in fact there is difference, you think your study was not successful but in fact it was!)
  • Type II Error = False Negative
  • Increasing the power (bigger sample size) decreases this error


Type III Error: Conclusions not supported by data


95% confidence interval: If it includes de value 1, it is not statistically significant.

  • The farther away form 1 the stronger the correlation (i.e., 9-10 or 0.1-0.2 has stronger correlation than 2-3 or 0.8-0.9)


Prevalence: # of patients having the disease in the population.

  • (It’s higher in long lasting diseases)


Incidence: # of newly diagnosed cases in a population in a given time period of time


SCREENING AND DIAGNOSTIC TESTS

  • Sensitivity: (analyzes the tests results (+) or (-) in the Patients with the disease/condition)
    • TP / (TP + FN) True positive rate:
    • The probability that a patient with the disease will have a positive test result.
    • SnOut: a sensitive test with a (-) result its good at ruling-out the disease
    • (You can trust Negative results)
    • High Sensitivity = Low False Negatives

  • Specificity: (analyzes the tests results (+) or (-) in the Patients without the disease/condition)
    • TN/(TN+FP) True negative rate:
    • The probability that a patient without the disease will have a negative test result
    • SpIn: a highly specific test with a (+) result its good at ruling-In the disease
    • (You can Trust Positive results)
    • High specificity = Low False Positives

Predicted Values are dependent on the prevalence of the disease:

  • Positive Predict Value: The probability that a person with a positive test result actually has the disease.
    • (Prevalence is directly proportional to PPV)
  • Negative predictive value: The probability that a patient with a negative test result really is free of the disease.
    • (Prevalence is inversely proportional to NPV)


Accuracy: (TP+TN)/(TP+TN+FP+FN)


Prevalence: (TP+FN)/(TP+TN+FP+FN)


STUDIES/DESIGNS:

  • Case Control: Retrospective
    • Takes patients with the disease and look in the past to see what factors contributed to develop the disease.
    • Uses Odds Ratio for the calculations: (TPxTN)/(FPxFN)

  • Cohort study: Prospective
    • Takes a group of pts exposed to a risk factor and a group of pts not exposed and follows them up for a couple of years to see how the disease develops, or if a drug has effect or not.
    • Uses Relative Risk for the calculations:
    • Incidence in exposed/incidence in unexposed
    • (TP/(TP+FP))/(FN/(FN+TN))

Clinical Trial: Randomized, Double blind, Multicenter, Placebo, control.

  • Meta-analysis:
    • Review and statistical
    • Combining of data from different studies
    • (Increases the power of any single study)
    • Also use (also uses Odds Ratio)

STATISTICAL TESTS:

  • Quantitative:
    • T test: Compares 2 groups (ex: means of weight b/t 2 groups)
    • ANOVA: Is a t-test for more than 2 groups.

Qualitative:

    • ''Non-parametric statistics: for qualitative data analysis. Race, sex, medical problems and diseases, medications)
    • Chi-square: compare 2 groups with categorical variables (obese patients with diabetes Vs. Obese patients without diabetes
    • Kaplan-Meyer: (small groups) estimate the survival rate

STATISTICAL TOOLS:

  • Mean:
    • The average of the Test
    • Central tendency in a Normal Distribution
    • The confidence interval of the mean gives the answer

Variance: The spread of data around the mean

  • Median: The middle value of a set of data.
    • Central tendency in a NON normal Distribution

  • Mode: The most frequent occurring value

Example: 2,3,5,5,7,8,9,11,12

Mode=5, Mean=6.8, Median= 7

Pages in category "Statistics"

Ad blocker interference detected!


Wikia is a free-to-use site that makes money from advertising. We have a modified experience for viewers using ad blockers

Wikia is not accessible if you’ve made further modifications. Remove the custom ad blocker rule(s) and the page will load as expected.