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1. Specialty - Reading List > Stats > Flashcards

Stats Flashcards

1
Q

an interval that has a certain probability of including the true population value.

A

confidence interval

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2
Q

increasing the sample size ____ SEM

A

DECREASES SEM

SEM = SD / √n

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3
Q

For sample sizes > ~30: The 95% CI

A

= sample mean ± 2 (sd/√n)
= sample mean ± 2 (SEM)

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4
Q

Variance of a proportion

A

Variance of a proportion = (P[1—P])/n
(provided n large, say > 100)
Where P = proportion that have heartworm
n = sample size = 200

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5
Q

Standard error of a proportion

A

Std error (SE) of a proportion = √variance

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6
Q

P value or Type I error (a)

A

The probability of having observed our data randomly - when the null hypothesis is true

Usually 0.05 (arbitrary)

No REAL difference to be found

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7
Q

Type II error (b)

A

Probability of accepting the null hypothesis when in fact the null hypothesis is false

Type II error depends on the true difference btwn populations

Occurs if there is no difference detected by the study!

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8
Q

Power of an experiment (1-b)

A

Given that there is a difference of a nominated amount btwn the two populations, the power is the probability of rejecting the null hypothesis at the a level of significance

Want the power to be at least
0.8

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9
Q

INCIDENCE RATE

A

Measure of the average risk of becoming a case during a specified time period

= number of NEW cases during a specified time period (often a year) / average population at risk during that time period

At least two visits are mecessary

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10
Q

ATTACK RATE

A

Incidence rate used in investigations of disease outbreaks

= number of NEW cases during a specified time period / initial population at risk

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11
Q

PREVALENCE

A

Prevalence focuses on disease states

= proportion of a population that is AFFECTED (may have had the disease for years) by disease at a given time

Dimensionless

Affected by both duration of disease and incidence - direct interpretation often difficult

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12
Q

relationship exists btwn incidence rate (I), average duration of a disease (D) and prevalence (P)

A

P (is proportional to) I x D

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13
Q

mortality is a specific form of

A

incidence rate
death rate

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14
Q

CASE FATALITY RATE

A

Numerator: deaths dt a given cause during a given time period

Denominator: total number of animals affected (ie cases)

CFR is measure of virulence or severity of a disease

Answers the question: “How many of those that get the disease will eventually die because of it during a given time period?”

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15
Q

PROPORTIONAL MORTALITY RATES

A

Often used when investigator has some mortality data but doesn’t know the population at risk (ie no denominator data is avail)

Numerator: number of deaths from a specified cause during a given time period

Denominator: all animals that died, regardless of cause

Answers the question: “Given that an animal has died, what is the probability that it died of a specific cause?”
Does not answer the question, “What is the risk of dying of a specific cause?”

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16
Q

RISK RATIO (RELATIVE RISK)

A

RR is usual way of comparing incidence rates

Formula: I1/I0
–I1 is incidence rate among “exposed group”
–I0 is incidence rate among “unexposed” group or reference group

Risk ratio > 1 association btwn “exposure” and disease

Risk ratio = 1 association btwn “exposure” and disease has not been demonstrated

Risk ratio < 1 negative association (protection) btwn the factor and disease

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17
Q

RATE DIFFERENCE (ATTRIBUTABLE RISK)

A

Formula: I1 – I0

Comparing incidence rates; measure of the absolute effect of exposure (1/time)

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18
Q

SENSITIVITY

A

the probability of a test correctly identifying those animals that are infected or have a specified condition

–Measure of the test’s accuracy w INFECTED animals
–Says nothing about the test’s accuracy w non-infected animals
–high Se = few false neg
–Poor Se = lots of false neg

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19
Q

SPECIFICITY

A

the probability of a test correctly identifying those animals that are not infected or which do not have the specified condition

–Measure of the test’s accuracy w non-infected animals
–Says nothing about the test’s accuracy w infected animals
–High Sp = few false positives
–low Sp = lots of false positives

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20
Q

If a disease has a v low prevalence, the Sp of the test can be estimated by

A

by assuming that virtually all the reactions are false positives and that the Sp would therefore be approximated by:
(c + d)/N

21
Q

PPV

A

answers the question:
“What proportion of the test positive animals really have the condition?”

a/(a+b)

22
Q

NPV

A

answers the question:
“What proportion of the test negative animals really do not have the condition?”

d/(c+d)

23
Q

3 types of bias

A

Selection bias
Information bias
Confounding

24
Q

selection bias

A

exists when the study group you have chosen is not representative of the target population

25
Q

information bias

A

can occur when the information collected is wrong or poorly interpreted.

incorrectly recorded data, poorly calibrated scales, different environmental exposures of control and tx groups

collecting better quality information from ‘case’ group than ‘control’ group in case-control study

26
Q

confounding bias

A

occurs when the association between a factor and the outcome of interest is distorted by the effect of an extraneous variable – a “mixing” of effects

27
Q

P-value

A

P-value is the probability of having observed our data (or more extreme data) when the null hypothesis is true.

28
Q

Power

A

The ‘power’ of an experiment is the probability that the null hypothesis will be rejected when there is a real difference of a given magnitude between treatments.

Generally, power of 80% is considered reasonable à we have an 80% chance of rejecting the null hypothesis if a difference exists.

29
Q

Clinical Trial

A

Planned experiment conducted in the field designed to assess efficacy of a tx in animals/herds by comparing the outcome observed under the test treatment, with that observed in a comparable group of animals/herds receiving a control tx

30
Q

Clinical Trial Requirements

A

Experiment is planned

Experiment involves the comparison of a test (new tx, new mgmt. procedure) and control (std. therapy, std. mgmt. procedure) tx

The study groups are comparable

Subjects are followed for a defined outcome

31
Q

Cohort Study Features

A

Investigator identifies group of animals that have the hypothesised “cause” and that are free from the disease of interest

A group of control animals that do not have the hypothesised “cause” of disease also identified

The two groups of animals are followed over a period of time to determine how many animals in each group develop the disease of interest. The incidence rates of the disease are calculated and the risk ratio is determined.

32
Q

Cohort Study Advantages and Disadvantages

A

+ Incidence rates can be directly calculated from the study
+ Study provides a complete description of the natural history of the disease. You will be following healthy animals and monitoring their progression into diseased states.
+ Allow the study of multiple potential effects of a given exposure.
+ Allow for good quality control.

  • Large no. of animals required to study rare diseases
  • In diseases w long induction or incubation period, there will be a long period of follow-up examinations
  • They are relatively expensive
  • Maintaining follow-up may be difficult
  • Control of extraneous variables can be difficult
  • Detailed study of the pathogenesis of the disease is rarely possible
33
Q

Features of a Case Control Study

A

Investigator starts by identifying a group of animals that have or had the disease in question (the cases)

A similar group of animals (the controls) that do not have the disease are identified

The past history of each group is investigated to determine how many animals per group had the “exposure” of interest.

Unlike cohort studies, case-control studies are retrospective

The objective in selecting controls is to select animals that are representative of the source population from which the cases were derived.

Cannot calculate incidence rates à cannot calculate risk ratios either

**An estimate of the risk ratio can be made from a case control study by determining the odds ratio

34
Q

Case control study advantages and disadvantages

A

+ Well suited to study of rare diseases or diseases w long incubation/induction periods
+Relatively quick and easy to conduct
+Require comparatively few subjects and are generally inexpensive
+Existing records can be used. There is no risk to the subjects in the study
+Allows for the study of multiple potential causes of the disease.

-Relies on recall or records for information on past exposure.
-Validation of the information you are told is difficult or sometimes impossible
-Control of extraneous variables is difficult
-Selection of an appropriate control group can be hard
-Incidence rates cannot be determined
-Detailed study of the pathogenesis of the diseases is rarely possible

35
Q

Cross Sectional Study Features

A

Investigator samples a population of animals (or farms)

Each animal is classified according to whether it has the disease at that time. Cross sectional studies are therefore measuring prevalence of a disease

Each animal is classified according to whether it has the exposure at that time

Analyses are carried out to identify relationships btwn the cause and the disease
–Quick, easy and “dirty” studies
–Because both cause and outcome measure at same time, impossible to tell w any certainty which came first

36
Q

Precise Study

A

relatively free from random error
REPEATABLE

37
Q

Valid Study

A

relatively free of systematic error and bias

if repeat over and over, the average result would be the “right” answer

38
Q

How to improve precision

A

1) Increasing number of subjects in study
2) Increasing the study efficiency

Imprecise estimate favours null hypothesis

Precise estimate more likely to be statistically significant

39
Q

bias

A

may be defined as any systematic error in the design, conduct or analysis of a study that results in a mistaken estimate of the parameter of interest.

40
Q

selection bias

A

Exists when the study group you have chosen is not representative of the target population.

Can occur due to:
a) Poor choice of control group
b) Poor choice of “sampling frame” (sampling frame is the sub-population in the target population from which the study subjects are drawn)
c) Non-responders and persons “excluded” from studies can cause selection bias

41
Q

information bias

A

Can occur when the information is wrong or poorly interpreted, leading to a misclassification of an exposure or disease.

Two broad categories of misclassification:
1. Differential misclassification: when an error in classification is more likely to occur in one group than the other
–E.g. recall bias
–Can bias the study in either direction

  1. Non-differential misclassification - when an error in classification is equally likely to occur in either group
    –Always biases a study towards the null hypothesis
42
Q

Confounding

A

Occurs when the association between a factor and the outcome of interest is distorted by an extraneous variable. To be confounding, the extraneous variable must have the following three characteristics:
1. Confounding variable must be a risk factor for the disease.
2. Confounding variable must be associated with the exposure in the population from which the cases derive
3. The confounding variable must not be an intermediate step in the causal pathway between exposure and disease.

43
Q

Sensitivity =

A

a / a+c

44
Q

Specificity =

A

d / b+d

45
Q

Accuracy =

A

a+d/a+b+c+d

dx correctly / all animals

46
Q

RR

A

a/a+b / c/c+d

47
Q

OR

A

AD/BC

48
Q

Prevalence =

A

a+c / a+b+c+d

total cases / total #

1. Specialty - Reading List (9 decks)

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