Sampling. Ivana Kolčić, PhD

Transcription

1 Sampling Ivana Kolčić, PhD

2 Basics Population Target population Sample from the target population Large enough (random error) Representative (external validity) Acceptable money and time

3 Representativenes The key for inference Sample is representative when it possesses the same characteristics as the population For example, the same age and gender structure, socio-economic characteristics, health indicators, ect. Acceptable level of representativeness = generalise study results We achieve representativeness by applying appropriate sampling design

4 Sample types Probabilistic samples: Random sample simple random sample stratified random sample Cluster sample Systematic sample Non-probabilistic samples: Convenient sample consecutive sample

5 Simple random sample Every element has the same probability to be chosen (probability sample) Big probability of getting a representative sample We can use it when we have access to the whole population, but we do not need so many participants We have to know all the members of the target population

6 Stratified random sample Guarantees greater level of representativeness Target population is first divided into homogenous groups, from which we are getting random samples

7 Cluster sample We are not sampling individually, but groups which form naturally (school children, factory workers, patients of a single doctor.) A research of attitudes about using drugs in high school pupils in Zagreb to gather information from all high schools would be quite complicated More easier would be to make a random selection of 10 schools, and then sample 100 pupils from each school

8 Systematic sample We use a system in getting the sample (for example, we will choose every 3rd or 10th patient who comes to the hospital) This approach is similar to simple random sampling, but we do not use real randomization

9 Systematic sample If we aim to choose 100 examinees from a group of 600 patients with coronary disease, we will : Take a list of 600 patients Since we need 100 examinees, we choose every 6th patient (600/100 = 6) We choose a random number from 1 to 6 (for example 2) We will sample every 2nd, then 8th, 14th, 20th, and so on, from the initial list of patients

10 Convenient sample In most cases not representative, but sometimes it is not important One of the most commonly used approaches in clinical research, but also in epidemiological field investigation of disease outbreaks Consecutive sample a type of convenient sample Different types of systematic error possible

11 Sampling Write detailed study protocol Geographic characteristics, time frame Demographic and clinical characteristics practical and representative Sampling criteria Inclusion criteria Exclusion criteria

12 Sampling Sampling criteria Research of birth weight and lenght of healthy newborns in Zagreb area Inclusion criteria: All newborns from Zagreb area (City of Zagreb and Zagreb County), delivered at the Department of Obstetrics and Gynecology in the year 2001 Exclusion criteria: To obtain a sample of healthy newborns from Zagreb area, we excluded (i) all newborns from parts of Croatia other than Zagreb and Zagreb County, (ii) stillbirths, neonatal deaths, multiple pregnancies and malformations that could have severely affected intrauterine growth (heart, kidney, brain or alimentary tract malformations, and severe genetic disorders), and (iii) pregnancies of unknown or uncertain gestational age Kolcic I, et al. Coll. Antropol. 2005:

13 Sampling The source of examinees? Clinical cases or From general population

14 Sampling Response rate Non-responders can be systematically different from responders (non-response bias); they are usually more frequently ill, have poorer socioeconomic status or are deprived Try to gather basic information from nonresponders Sample large enough! calculate before the study begins!

15 Sampling To reduce non-response: Repeated contacts with examinees Less invasive or uncomfortable methods Personal contact between researcher and examinees Booklet with info Reimbursement (travelling costs) Give results of the tests..

16 Sample size estimation How many examinees? oftenly asked important question not a simple question to answer! 2 aproaches: graphical estimation Altman s nomogram mathematical formula

17 Sample size estimation 3 parameters needed clinically relevant differrence or statistical significance level (α=0.05 or 0.01) power (1-β)

18 Sample size estimation

19 Sample size estimation