Term
Two basic types of sampling 

Definition
 probability based
 non probability based



Term

Definition
¤The entirety.
¤All the members/elements you can think of within a specific category.
¤Size and characteristics depend on what one is thinking of studying 


Term
Char. of probability sampling 

Definition
 always for quantitative research
 sampling units have known probability of being selected
 involves statistical analysis
 results can be generalized
 sample size calculation is involved



Term
Char. of nonprobability sampling 

Definition
 usually for qualitative research methods
 no such thing as known probability
 doesnt involve statistics (except status quo sampling)
 results are not intended to be generalizable
 sample size calculation is not involved



Term

Definition
¤The act of taking a sample
¤a process of selecting what/who will participate in a study 


Term

Definition
The complete list of all elements from where you select what/who you want to study 


Term

Definition
¤Part of the whole
¤A methodical selection of the required number of sampling units from a defined population 


Term

Definition
population about which information is required 


Term

Definition
the population that is actually listed in your sampling frame, sometimes target population and study population are the same population 


Term

Definition
¤Simple random sampling
¤Systematic sampling
¤Twostage sampling (cluster sampling)
¤Stratification 


Term
Effect of random sampl,ing 

Definition
 ensures equal chance of getting selected
 those I selected can represent those who have not been selected
 should have representatitive sample of population where it was collected



Term

Definition
¨The most basic sampling design.
¨If you can make a complete list of your target population then you can use simple random sampling
¨The idea is to assign a number to each of the units in a population and then use a random number generator of some sort to choose the respondents for the analysis. 


Term
Process of simple random sampling 

Definition
¨Obtain a sampling frame that contains all the units in the study population (walking door to door, use census, etc.).
¨Number each unit from 1 to N—the study population size.
¨Select sampling units using a sequence of random numbers between 1N using a random number table or calculator or software (Excel, Stata)
The most practical way of doing this for anything more than very small numbers is to hold the list electronically (in Stata) and generate a column of random numbers beside it. Then sort the list by the random numbers and take the first n units (n = desired sample size). 


Term
random number tables: when to use 

Definition
when in the field and cannot use computerized simple random samples 


Term
random number table: Process 

Definition
¨Number each member of the study population.
¨Determine study population size (N).
¨Determine sample size (n).
¨Determine starting point in table by randomly picking a page and dropping your finger on the page with your eyes closed.
¨Choose a direction in which to read (up to down, left to right, or right to left).
¨Select the first n numbers read from the table whose last X digits are between 0 and N. (If N is a two digit number, then X would be 2; if it is a four digit number, X would be 4; etc.).
¨Once a number is chosen, do not use it again.
¨If you reach the end of the table before obtaining your n numbers, pick another starting point, read in a different direction, use the first X digits, and continue until done. 


Term
Difficulties in practicing simple random sampling 

Definition
 too many households
 widely distributed households
 no lists of households readily available
 high transport cost
 difficult management
 requires complete sampling frame
 expensive with widely distributed population even with complete sampling frame
 SRS usually practical only for small compact populations



Term

Definition
¨Every Kth unit in a list is selected for inclusion in the sample
¨To be effective, there needs to be no systematic order in the list
¤Be very careful if names are listed alphabetically.
¤If the interval chosen is 12 and you had monthly data, then you would always choose data from the same month.
¨Empirically identical to simple random sampling 


Term
When is most useful to use systematic sampling 

Definition
no precise sampling frame 


Term
Advantages and disadvantages of systematic random sampling 

Definition
¨Advantages
¤You can start without having a precise sampling frame
¤Easier to keep track in the field
¤With an inherent trend in the sampling frame, representation is ensured from minimum to maximum values of the trend.
nListing according to population size—guarantee good spread of people from urban and rural areas
nOrder by value of housing—sample would include a good spread of rich and poor
¤Good approximation to SRS
¨Disadvantages
¤Any cyclicality or periodicity in the in the list and you are in trouble.
¤Or large inequality in the list may get you into trouble. 


Term
definition of two stage cluster sampling 

Definition
a 2stage cluster sample is obtained by first selecting a probability sample of clusters (Primary sampling Unit) and then selecting a probability sample of elements from each sampled clusters 


Term
When is it most desireable to do two stage cluster sampling? 

Definition
¤Large survey covering large geographic area involving sampling of Housing Units (e.g. demographic health surveys)
¤A frame listing all elements in the population may be impossible or costly to obtain where as listing all clusters and knowing their properties is easier. 


Term
Difficulty with two stage sampling 

Definition
¨Need to ensure each individual has the same chance of being selected.
¨Problem: If we select both first and second stage units (e.g. villages then household) using SRS, and take the same number of hhs per village, we have a problem. (aka some people have higher chance of being sampled than others)
Solution: Sample PSUs with probability proportional to size (PPS), so larger villages are more likely to be selected. Then take same number of hhs from each cluster selected 


Term
Steps to cluster sampling 

Definition
¨Bangladesh has about 100 HHs in clusters of enumeration areas (EAs) used by the census bureau
¨Sampling frame of EAs is accessible. EAs are the Primary sampling unit (PSU)
¨Take random sample of a desired number of EAs
¨In each EA list HHs= sampling frame for each EAs
¨ Randomly select HHs from each 


Term
Two stage cluster sampling using population proportional to size (PPS) model 

Definition
¨True PPS sampling produces a selfweighting sample, each household has the same chance of being selected—no weights are required.
¨PPS sampling involves listing units (towns, villages etc.) with their population size.
¨In doing this we may select many persons from a large town and few (or even none) from a tiny village—but this is correct—it is proportional to size. 


Term
characteristics of stratified sampling 

Definition
¨Break up the population into homogenous nonoverlapping groups (strata) before sampling.
¤Why? We want to get a reasonable estimate of something (e.g. neonatal mortality) in different subgroups in our population—say by region or urban rural
¨May be used in conjunction with simple random sampling, systematic, or cluster sampling 


Term
Primary reasons for doing stratified sample design 

Definition
¤To potentially improve representativeness, in terms of the stratification variables, by gaining greater control over the composition of the sample.
¤To ensure that particular groups within a population are adequately represented in the sample 


Term
What determines how we stratify in sampling? 

Definition
¨The choice of stratification variables depends on the variables that matter for responses. In most public health research, natural candidates are race, income, education, gender, location, etc.
¨The sampling fraction generally varies across strata (i.e. some individuals will have more chance of being in the sample) Therefore we would need to make adjustments for this during our data analysis using sampling weights. 


Term
Proportionate stratified sampling vs. disproportionate 

Definition
¨Proportionate stratified sampling:
¤when sampling units in the strata are selected proportional to their representation in the source population
¨Disproportionate sampling:
¤deliberately increasing the size of sampling units selected from a particular strata so they represent a disproportionate figure in the sample compared to the source population. 


Term
disproportionate sampling: how to compensate for it? 

Definition
¨Researchers must adjust unequal probability sampling data to compensate for the differences in the likelihood of some population members appearing in the sample
¨You make this adjustment by weighing certain observations more than others in the estimations. 


Term
What is lot quality assurance sampling and its advantages 

Definition
 can be used locally at the level of "supervision area" to ID priority areas or indicators that are not reaching average coverage or anc established benchmarks
 can provide an accurate measure of coverage or health care system quality at a more aggregate level
 can be used for quality assurance using a minimal sample, maximum security principle


