Research Methodology 3: RCTs Flashcards

(30 cards)

1
Q

Define a RCT

A

RCT: a study in which participants are allocated randomly between an intervention
(e.g. treatment) and a control group (e.g. no treatment or standard treatment)

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2
Q

why are trials conducted?

A
  1. Safety
    • Ascertain the safe dose of a
    new drug.
  2. Efficacy/ Effectiveness
    • Demonstrate efficacy of new
    drug
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3
Q

why do we randomise ?

A
When looking at cause-effect relationships, randomisation allows all
random factors (confounders) apart from the proposed cause to be
held constant between groups.
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4
Q

define confounder

A

A confounder is a variable that influences both the dependent
variable and independent variable causing a spurious association.

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5
Q

what does randomisation do

A

• Randomisation ensures all potential confounding variables (known
and unknown) will be distributed by chance across all study groups

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6
Q

Define equipoise

A

Clinical equipoise means that there is genuine uncertainty in the expert
medical community over whether one treatment will be more beneficial
than another.

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7
Q

what makes a good RCT?

A

Internal validity – is the IV causing the DV in this study?

External validity – to what extent can these findings be generalised to
other people, situations and times?

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8
Q

Define bias

A

In statistics - ‘a tendency of an estimate to deviate in one direction
from a true value’

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9
Q

list 4 types of bias

A

selection
performance
attrition
observer/detection

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10
Q

define selection bias

A

Systematic differences between baseline characteristics of groups that
are compared
Study sample does not represent target population

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11
Q

define performance bias

A

Systematic differences between groups in the care that is provided, or in
exposure to factors other than the interventions of interest

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12
Q

define attrition bias

A

Systematic differences between groups in withdrawals from a study
• Can cause systematic differences between groups – e.g. one
treatment has more side effects than another.

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13
Q

define observer/detection bias

A

Outcome measure does not adequately capture outcome of interest
• Systematic differences between groups in how outcomes are determined
Not adequately capturing the outcome of interest

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14
Q

Define intention to treat

A

– analysed in treatment group they were

randomised to, whatever happens later.

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15
Q

Define on-treatment analysis or per protocol analysis

A

only analyse

patients who finish the treatment according to the study protocol.

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16
Q

how many types of trials can you blind and describe who is blinded in each?

A

open: no one
single: patient is blinded
souble: pt and dr blinded
triple: pt/dr/investigators

17
Q

what is the significance level?

18
Q

what is the power of the study accepted at ?

19
Q

If i observe a difference and there is one what is this?

20
Q

if i observe no difference and there isn’t one what is this ?

A

well designed

21
Q

what is a type 1 error

A

observe a diff but no diff

22
Q

what is a type 2 error

A

observe no diff but there is a diff

23
Q

define the p value

A

The P-value is the probability of observing the result you got, or more
extreme, if the null hypothesis were true,
where the result is a statistic estimated on the data you have collected in your
study.

24
Q

why do we calculate sample size?

A
Too few participants... If you get a null result, you don’t know
if you have:
• Evidence of no effect
• or simply…
• No evidence of an effect
too many = not ethical
25
what does parametric data assume
normally distributed
26
define positive and negative skew
look at the tables
27
what do you use if your data is skewed? descriptive analysis
median and IQR
28
if data is normally distributed which statistical tests would you use?
``` t test (scale) chi sqaured (categories) anova (scale) ```
29
what assumptions are made for a t test
random sample independent observation normally distributed variances for each group are equal
30
what test is used if data is non-parametric
Mann-Whitney U/Wilcoxon Rank Sum replace t-test