Tiêu đề POPULATION & SAMPLING .pdf ✅

CHAPTER SAMPLING (SAMPLING DESIGN) POPULATION: Target population or Reference population e Entire group (full set) of study subjects having some common characteristic(s). e Entire group (full set) of study subjects about which we desire information. e Full set of study subjects on which study results are generalized (extrapolated). e It is synonymous with target population or reference population. 1 e.g. All doctors of Bangladesh, All medical colleges of Bangladesh, 5-10 years children of Bangladesh etc. Homogeneous Population Population with little variation in the characteristics among the population units. e.g. All female muslim internee doctors of Dhaka Medical College Hospital. Heterogeneous Population Population with wide variation in the characteristics among the population units. e.g. All students of Dhaka University. All fishes of the Bay of Bengal. Finite Population Number of units in population is finite and countable. e.g. Number of students in class, leprosy patients in community Doctors of Bangladesh. Infinite Population Number of units in population is infinite (endless) and not easily countable. e.g. Stars in sky, mosquito in Dhaka city, hilsha fish in river Padma. Static Population Population unit do not change frequently. e.g. Stars in sky Dynamic Population Population unit changes frequently e.g. hospital patients. SAMPLE 1 e Part of population or subset of population which represent the population. e It is always finite. SAMPLING: Sampling technique/Sampling design 1 e Process of selecting a sample from the population. e The method of selecting a suitable representative segment of population. SAMPLING POPULATION: Study population or Accessible population 1 • It is the convenient sub group of target population from which sample is actually taken. • Ideally target population and sampling population should be same specially if population size is small e.g. study on students of DMC. Here sample will be taken from total DMC students which is the target population as well. The question of sampling population arises if target population found to be very large, widely scattered, unavailable or inaccessible. e.g. I. To study the prevalence of disability among 5-10 years children of Bangladesh, total list of these children may not be available. Since they are readily available in primary 109
abc of methodology rese•tch biostatistics school: so researcher decide to use primary school children as the sub group for sampling. So here, target population is all 5-10 yrs children in Bangladesh and sampling popu)ation is 5-10 yrs children who attend primary school. 2. If vou like to do a research on diabetic patients of Bangladesh, total list of these patients may not be available: so it will be difficult to make access to this population for sampling. In BIRDEM hospital every day about 5000 diabetic patients attend CDPD from all over the Bangladesh; so from this group of patients sampling can be done for the research. Therefore in this instance the target population is all diabetic patients of Bangladesh & sampling population is the diabetic patients attending BIRDEM hospital. Extrapolation or Generalization SAMPLING UNIT Target population by common sense-judgment Sampling population or Study population by sampling Sample Conclusion Unit of population chosen for selecting sample. e Every member of a sample. SAMPLING FRAME: Source list e List (database) of all sampling units of the population. e List of sampling units constituting the population. e.g. 1. From the population of 1000 students of the DMC, for any research purpose if we select a sample of 100 students; every student will be sampling unit and the total list Of all 1000 students in DMC will be the sampling frame. 2. If you like to do a research on thana health complexes (THC) of Bangladesh; out Of total 500 THC you may decide to select a sample of 50 THC. Every THC is sampling unit & the total list of 500 THC is the sampling frame.
abc methodology & of research biostatistics (Observational unit) 1 An object (or person) on which outcome variable is measured. Sampling unit and elementary unit are sometimes identical but sometimes different. e.g. I. Prevalence of malnutrition among under 5 year children of Bangladesh. Here the population is all under 5 year children of Bangladesh. This is a very big populaton & their total list is not available or not possible to make. So, researcher may decide to use the list of all 68000 villages of Bangladesh for sampling purpose. From this list of villages a sample of some villages will be selected and all under 5 year children of these selected villages will be included in the study. So, here sampling unit is village and elementary unit is under five year children of selected villages. 2. Study on students of DMC: Here target population & sampling populaiton is same. So here every student is sampling unit as well as elementary unit. ADVANTAGES (REASONS) OF SAMPLING I. Quick determination that make the result timely. 2. Cost effective (less expenditure). Saves time & labor. 3. It make possible of something impossible for a big sized population. In a big population (e.g. all under 5 year children of Bangladesh) it is physically impossible to conduct a study including all members. In that case selecting a representative sample is the only way to get the required information. z 4. Good for partly accessible or difficult to access population e.g. prisoners. 5. Sometimes more accurate & more reliable because more accurate methods, better care & better rapport can be exercised on a small group for intensive and exhaustive data collection. 6. Even if total population studied by lot of money and time; it would be still incomplete because future cases can't be studied and it will fail to guarantee reliability. So it is wise to go by sampling because empiricism permits the findings on existing cases to be used on the future cases or remaining cases of population. DISADVANTAGES OF SAMPLING: Sampling error (sampling variation) 1 Sampling error is the variation among the values of different samples taken from the same population. It happens because the composition of different samples are different. A sample is expected to be representative to the population from which it comes. Although there are several methods for getting representative sample, no method guarantees a truly representative sample of the population. Therefore always there is scope of sampling error among the samples. It is possible to take care of sample size and sampling to reduce sampling bias (systemic error) but sampling error can not be eliminated because it is unavoidable and happen as an error due to by chance. so sampling error arise due to the fact that only a part of population as sample has been used to estimate population parameter. Sampling error is absent in census. Sampling error is synomymous with sampling variation, random variation, random error. REPRESENTATIVE SAMPLE 1 • A sample having its base line characteristics and variability nearly identical to the base line characteristics and variability of the population under study. 111
abc of resent-ch biost*tiqticg A somp)e where vnyanl>le Of interest shows same (itstribution as it is in the POPUIation. Representative sample negligible sampling error. So representativeness of a *ample makes it possible to generalize the sample fmdings over the population; that means to regard sample result as population result. A representative sample will be mirror image of population and it is ensured by selecting z sample randomly (unbiasly). 's' Sample failb to givc valid result if non-representative & fails to give reliable result if it is small. TYPES OF SAMPLING TECHNIQUE A. Random sampling (probability sampling): z The technique where every unit of population (every sampling unit) will have equal chance to be included into the sample. It is based on random selection of sampling units from population by any kind of lottery or by use of random number table. z Here no sampling unit gets preference over the other or no sampling unit is left out intentionally to push the result in the direction that the researcher wants to see. There is more chance for the selected sample to be representative and generalizable. Common types of random/probability sampling. Simple random sampling (SRS) or Unrestricted random sampling Systematic random sampling or Serial/Quasi random sampling Stratified random sampling Cluster sampling or Block sampling Multi stage sampling or Area sampling Multiphase sampling Of different random sampling technique, the simple random sampling is the most unbiased if correctly carried out. Others are in fact the modifications, adopted when simple random sampling is not practical. B. Non random sampling (non probability sampling or selective sampling): The technique where every unit of population (every sampling unit) will not enjoy equal chance to be included into the sample. It is a subjective rnethod of sampling where sampling units are selected from population deliberately by choice or by personal judgment without any lottery. Selected sample fails to be representative and generalizable in true sense. Common types of non random/nonprobability sampling. Convenient sampling (accidental/incidental/opportunity sampling) Purposive sampling (judgment sampling) Quota sampling Snow ball sampling Consecutive sampling 112