Biostatistics types of studies
Download
1 / 14

Biostatistics ~ Types of Studies - PowerPoint PPT Presentation


  • 121 Views
  • Updated On :

Biostatistics ~ Types of Studies . Research classifications. Observational vs. Experimental Observational – researcher collects info on attributes or measurements of interest, but does not influence results.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'Biostatistics ~ Types of Studies' - brook


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

Research classifications l.jpg
Research classifications

  • Observational vs. Experimental

    Observational – researcher collects info on attributes or measurements of interest, but does not influence results.

    Experimental – researcher deliberately influences events and investigates the effects of the intervention, e.g. clinical trials and laboratory experiments.


Research classifications3 l.jpg
Research classifications

  • Prospective vs. Retrospective

    Prospective – data are collected forwards in time from the start of the study, e.g. experiments & survival studies.

    Retrospective – data refer to past events and may be acquired from existing sources such as hospital records or by interview, e.g. case-control studies & cohort studies.


Research classifications4 l.jpg
Research classifications

  • Longitudinal and Cross-Sectional

    Longitudinal – investigates changes over time, e.g. survival studies.

    Cross-sectional – individuals are observed only once, e.g. surveys.


Example 1 cholesterol drug test i e phase iii clinical trial l.jpg
Example 1 – Cholesterol Drug Test(i.e. Phase III clinical trial)

How might we proceed?


Example 2 determine whether age at 1 st pregnancy is a risk factor for cervical cancer l.jpg
Example 2 – Determine Whether Age at 1st Pregnancy is a Risk Factor for Cervical Cancer

How might we proceed?


Example 3 design an experiment to compare two treatments of ovarian cancer patients l.jpg
Example 3 – Design an experiment to compare two treatments of ovarian cancer patients.

How might we proceed?

What are some potentially unique issues/challenges for such a study?


Slide8 l.jpg
Example 4 – Determine if right heart catheterization (Swan-Ganz line) increases risk of 30-day mortality amongst heart patients.

How might we proceed?


Selection of controls in case control study l.jpg
Selection of Controls in Case-Control Study (Swan-Ganz line) increases risk of 30-day mortality amongst heart patients.

Goal: Want controls as similar as possible to cases.

What is typically done:

  • Use patients hospitalized for other reasons

  • Matching according to some criteria. Only helpful if variables used are strongly related to both the risk factor and the outcome of interest.

  • Usually have more controls than cases, especially with rare events. Can have multiple matched controls per case.


Selection of cases l.jpg
Selection of Cases (Swan-Ganz line) increases risk of 30-day mortality amongst heart patients.

  • Generally must meet some entrance criteria (but may have to take what one can get)

    Need to take into account or realize that all cases are not similar in cause disease, exposure to risk factor, degree of disease, etc…


Bias in case control studies l.jpg
Bias in Case-Control Studies (Swan-Ganz line) increases risk of 30-day mortality amongst heart patients.

  • A diseased person is likely to recall more risk factors (especially widely publicized ones) than a healthy person. This is called perceived risk.

  • Missing data in medical records

  • Presence of risk factor may increase chance of detection

  • In accuracy in reporting of exposure, e.g.

    How much did you drink?

    How much did you smoke?

    Etc…


Cohort studies l.jpg
Cohort Studies (Swan-Ganz line) increases risk of 30-day mortality amongst heart patients.

  • Method of choice for observational studies

  • The essence of the cohort study is identify a group of subjects and then follow them up to see what happens (longitudinal).

  • Compare to age at 1st pregnancy and cervical cancer study.

  • Quality of data recording can be carefully controlled.


Problems with cohort studies l.jpg
Problems with Cohort Studies (Swan-Ganz line) increases risk of 30-day mortality amongst heart patients.

  • Selection of subjects (lots of issues)

  • Loss to follow-up (biggest problem)

  • Surveillance Bias – high risk group might be studied more carefully. Best approach is to investigate all subjects identically and assessors should be “blinded”.


Cross sectional study l.jpg
Cross-Sectional Study (Swan-Ganz line) increases risk of 30-day mortality amongst heart patients.

  • All information is collected at the same time.

  • Sampling is always an issue

  • Nonresponse bias

  • Volunteer bias

  • As with all observational studies it is hard if not impossible to establish causation!