From study objectives to analysis plan Helen Maguire.

From study objectives to analysis plan

Helen Maguire

don’t get bogged down -or stuck …

its logical

the keys to successful research

• get the research question crystal clear

• write a clear outline (concept paper)

• involve stakeholders

• talk to people

• revise again and again

• get the research question crystal clear

avoid X

• too ambitious/ unfocussed• unsound unscientific basis for hypothesis • not clear what impact the findings will have in the

field ..• no clear plan of next steps• not ethical• lacking appropriate expertise

The ad-hoc approach to conducting an epidemiological study

Before data collection• I want to do a study

– I am not clear about the objectives

• I prepare a questionnaire– I am not clear about

what information I need

• I collect data– I am not clear what I

will use for what

After data collection

• I come back with data – I realize they are

difficult to analyse

• I analyse the data– I realize it is difficult to

interpret the results

• I interpret the results– I realize it is difficult to

use them

Sound familiar?

The life cycle of an epidemiological investigation

Identifying data needs

Spelling out the research question

Formulating the study objectives

Planning the analysis

Preparing data collection instruments

Analysing data

Drawing conclusions

Formulating recommendations

Involving the programme

Collecting data

Analysis plan

analysis plan: road map

1. choose a design to identify key indicators

2. identify parameters (variables) needed for indicators

3. prepare the analysis

4. estimate sample size

Objectives

epietmobile



2. identify parameters needed for indicators



Design and indicators

• what sort of designs do you know?

• what do you need to consider to help you decide which one to use?

choosing a suitable study design

i will try and update this

Epidemiologicalstudies

Observational(non-intervention)

Data fromindividuals

Data from groups

Descriptive Analytic

Ecological study

Descriptive Analytic

Cross sectional study Cohort studyCase control

study

Data from groupsData fromindividuals

Experimental(intervention)

Community trialClinical trial,

individual fieldtrial

what to consider when choosing a study design

• is the study descriptive or analytical?– are you comparing groups?

– are you estimating a frequency?

• is the outcome (e.g., disease) acute or chronic– prevalence data for chronic disease

– incidence data for acute outcomes

• is it common or rare?– case control for rare outcomes

– cohort / cross sectional for common outcomes


testing a hypothesis estimating a quantity

• determine whether hepatitis C is more common in people who inject drugs (PWID) – hypothesis testing

– crude objective, smaller sample size

• estimate the relative frequency of hepatitis C infection in PWID vs others – quantity estimating

– more elaborate objective, larger sample size

Objectives

clearly identify the study population

• this is different from the sample you will study

examples - what design?

• who is most likely to get wound infection after appendicectomy?

• what lifestyle factors are associated with acquiring hepatitis C?

• what experiences do patients with rare disease such as MDR TB have using NHS services?

what design • who is most likely to get wound infection after

appendicectomy

– cohort study

• what lifestyle factors are associated with acquiring hepatitis C

– case-control study comparing those with hep C and those without

• what experiences do patients with rare disease such as MDR TB have using NHS services

– qualitative study or survey with open ended questions



2. identify variables needed for indicators



Parameters

what indicators ?• who is most likely to get wound infection after

appendicectomy

– cohort study

• what lifestyle factors are associated with acquiring hepatitis C

– case-control study comparing those with hep C and those without

• what experiences do patients with rare disease such as MDR TB have using NHS services

– qualitative study or survey with open ended questions

estimating the relative frequency of meningococcal carriage in children of parents

who smoke vs others

• … from the objectives:– analytical approach: compare two groups

– chronic condition: prevalence data

– common condition: survey

• study design:– analytical cross sectional study

• indicator:– ratio of prevalence of meningococcal carriage among

children of smokers vs others


what’s needed to calculate the indicator?

• list the indicators that the study will generate – proportion with carriage for categorical variables,

prevalence rate, prevalence ratios

• remember:– outcome variable(s)– “covariates” including

• potential risk factors• potential confounders

• identify the information needed to calculate the indicators– numerators and denominators

• example: number carrying / total children

Parameters

....from indicators to variables

• identify variables that enable you to get your indicator – information “meningococcal C vaccination status”

can be collected by review of cards or interview of the mother

• choose the best variable – review standardized guidelines (e.g., WHO, CDC)– e.g. how to measure smoking

• plan data collection methods for each variable– record review – interview– observation– laboratory data

Parameters

covariate measurement for meningococcal carriage study among

children of smokers vs others • potential risk factors

– income(validated field methods)

– ethnic group– education– area of residence– vaccination against Men C

• potential confounding factors– age– sex

Parameters

analysis plan road map





Analysis

rationale for preparing the data analysis in advance

• focus on the objectives of the study

• avoid multiple comparisons

• avoid comparisons for which the study was not designed ….(tempting as it is..)

• ensure data collected can be analyzed– “Other, specify: _____” ?? .. groups that cannot be

analyzed

• save time– filling dummy tables speeds data analysis

Analysis

a word about coding

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a word about coding

• binary coding (usually):– “1” is yes– “0” is no

• gender (usually):– “1” is male– “0” or “2” is female

• age (or any categorical ordered var.)– by percentiles– by common sense

27

preparing the analysis, stage by stage

• recoding stage– example: age into age groups

• descriptive stage– calculate prevalence or incidence

• analytical stage – univariate, stratified and multivariable analysis– prepare empty (dummy) tables (shells) now

Analysis

initial stage of analysis meningococcal carriage according to smoking status

• recoding stage – create outcome data with laboratory results

-carriage Yes/No

– recode smoking data

dichotomize quantitative smoking variable (how many do you smoke a day (0,1,2,3…20))

-smoke Yes/ No

• descriptive stage– calculate prevalence of meningococcal carriage

Analysis

analytical stage meningococcal carriage

according to smoking status of parent • univariate analysis

– prevalence of outcome by age, sex and residence– prevalence of outcome by smoking (potentially

examine dose response effect)

• stratified analysis – prevalence of outcome by smoking, stratified for

age, sex and residence

• multivariable analysis (adjusted risk/rate ratio) – logistic regression model– binomial regression

Analysis

dummy table for meningococcal carriage study – proportion carriage by factor

(analytical stage) *

Prevalence

Prevalence ratio (95% confidence

interval)exposures/factor exposed unexposed

female sex XX/XX (xx%) XX/XX (xx%) XX (XX-XX)

caucasian XX/XX (xx%) XX/XX (xx%) XX (XX-XX)

age > median XX/XX (xx%) XX/XX (xx%) XX (XX-XX)

smoking parent XX/XX (xx%) XX/XX (xx%) XX (XX-XX)

residence urban area

XX/XX (xx%) XX/XX (xx%) XX (XX-XX)

*variables dichotomized






Sample size

the analysis plan determines the sample size

• choose the study design– cohort, case control or survey

• determine the level – descriptive or analytical

• common mistake– designing a descriptive study – making comparisons for which the sample size is

insufficient

Sample size

sample size for study on meningococcal carriage

• study design– analytical cross sectional survey

• level– analytical

– need to

• use prevalence ratio for sample size estimation

Sample size

take home messages

• clarify again - precise focussed objectives

• choose a design - identify the indicator

• know the parameter (variable) you want before you think about how to get information about it

• know where you go with the analysis– the planned analysis drives the data needs and not

the reverse

• work out sample size from all of the above

• thanks for your attention

From study objectives to analysis plan Helen Maguire.

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