Mandatory reading

PHOTO BY HAFM JANSEN7

CHAPTER SEVENDeveloping a Sampling StrategyTopics covered in this chapter:Sampling considerations in qualitative studiesSampling considerations in quantitative research surveysO ne cannot overemphasize theimportance of developing an appropriate designing a sample for qualitative or quantitative research. It also gives examples ofsample for the type of research design how different strategies have been used toselected. Although qualitative and quantita- fit the specific needs and circumstances oftive research use different approaches for research projects.selecting the individuals or groups to bestudied, in all studies it is crucial to plan SAMPLINGthe sampling strategy carefully. Particularly C O N S I D E R AT I O N S I Nin the case of population-based surveys, a Q U A L I TAT I V E S T U D I E Spoorly selected sample may harm the cred-ibility of a study, even if the rest of the There are no hard and fast rules for samplestudy is well executed. sizes in qualitative research. As Hudelson Qualitative studies generally focus in points out, “The sample size will dependdepth on a relatively small number of on the purpose of the research, the specificcases selected purposefully. By contrast, research questions to be addressed, whatquantitative methods typically depend on will be useful, what will have credibility,larger samples selected randomly. These and what can be done with available timetendencies evolve from the underlying pur- and resources.”2pose of sampling in the two traditions of In qualitative sampling, the selection ofinquiry. In quantitative research, the goal respondents usually continues until theof sampling is to maximize how represen- point of redundancy (saturation). Thistative the sample is so as to be able to means that when new interviews nogeneralize findings from the sample to a longer yield new information and alllarger population. In qualitative inquiry, the potential sources of variation have beengoal is to select for information richness so adequately explored, sampling may stop.as to illuminate the questions under study.1 For most qualitative studies, 10 to 30 inter- This chapter discusses the major issues views and/or 4 to 8 focus groups will suf-that should be taken into account when fice. Table 7.1 summarizes a number of A Practical Guide for Researchers and Activists 105

CHAPTER SEVEN TABLE 7.1 TYPES OF SAMPLING STRATEGIES FOR QUALITATIVE STUDIES Type of Sampling Purpose Example Intensity sampling To provide rich information from a Interviewing survivors of date rape few select cases that manifest the to learn more about how coerced phenomenon intensely (but are not sex affects women’s sexuality. extreme cases). Deviant case sampling To learn from highly unusual mani- Interviewing men who do not beat festations of the phenomenon in their wives in a culture where wife question. abuse is culturally accepted. Stratified purposeful sampling To illustrate characteristics of particu- Interviewing different types of serv- lar subgroups of interest; to facilitate ice providers (police, social work- comparisons. ers, doctors, clergy) to compare their attitudes toward and treatment of abuse victims. Snowball or chain sampling (Locate To facilitate the identification of Finding commercial sex workers to one or two key individuals, and hard-to-find cases. interview about experiences of then ask them to name other likely childhood sexual abuse by getting informants.) cases referred through friendship networks. Maximum variation sampling To document diverse variations; can Researching variations in norms (Purposely select a wide range of help to identify common patterns about the acceptability of wife beat- variation on dimensions of interest.) that cut across variations. ing by conducting focus groups among different sub groups: young urban women, old urban women, young rural men, old rural men, women who have been abused, women who have not experienced abuse. Convenience sampling (Select who- To save time, money, and effort. Forming focus groups based on ever is easiest, closest, etc.) Information collected generally has who is available that day at the very low credibility. local community center, rather than according to clear criteria. Criterion sampling To investigate in depth a particular Specifically interviewing only “type” of case; identify all sources abused women who have left their of variation. partners within the last year in order to better understand the variety of factors that spur women to leave. (From Patton, 1990.3) different approaches to qualitative sampling. their intimate relationships. They wanted In qualitative research, the sampling to understand the beliefs and attitudes that strategy should be selected to help eluci- existed in Nicaraguan culture that sup- date the question at hand. For example, ported violent behavior toward women. researchers with the Nicaraguan organiza- More importantly, they wanted to know if tion Puntos de Encuentro embarked on a there were any “benefits” of nonviolence project to collect information useful for that could be promoted to encourage men designing a national media campaign that to reconsider their behavior (Box 5.6). called on men to renounce violence in Rather than concentrating on collecting106 Researching Violence Against Women

D E V E L O P I N G A S A M P L I N G S T R AT E G Yinformation on the norms and attitudes of“typical” Nicaraguan men, the researchersdecided to use “deviant case” sampling andconcentrate on interviewing men who hadalready had a reputation for being nonvio-lent and renouncing machismo.4 They wereinterested in finding out from these menwhat benefits, if any, they perceived fromthis choice, and what life-course events,influences, or individuals pushed them inthis direction. The goal was to investigatewhat aspirations and life experiences helpcreate “healthy” intimate partnerships. Thefindings were used to design an informa-tion campaign aimed at recruiting moremen to a nonviolent lifestyle.SAMPLINGC O N S I D E R AT I O N S PHOTO BY HAFM JANSENI N Q U A N T I TAT I V ERESEARCH SURVEYSIn contrast to qualitative research, whichgenerally uses nonprobability or “purpo-sive” sampling, quantitative research relies violence, the study results A probability or representativeon random sampling of informants. A would be biased towards sample is a group ofprobability or “representative” sample is a women who work at home. informants selected from thegroup of informants selected from the pop- One way to reduce this partic- population in such a way thatulation in such a way that the results may ular bias would be to return to the results may be generalizedbe generalized to the whole population. homes at night or on week- to the whole population. When a sample is referred to as ran- ends to increase the likelihooddom, it means that specific techniques of reaching all women.have been used to ensure that every indi- The way in which the sample is chosenvidual who meets certain eligibility criteria affects its generalizability, or the extent tohas an equal probability of being included which the situation found among a particu-in the study. Failure to adhere to these lar sample at a particular time can betechniques can introduce error or bias applied more generally. There are manyinto the sample, which may lessen the techniques for sampling, each with its ownvalidity of the study. For example, if a tradeoffs in terms of cost,household survey on violence only con- effort, and potential to gener- When a sample is referredducted interviews during the day, then the ate statistically significant to as random, it means thatrespondents most likely to be included in results. Some strategies, such specific statistical techniquesthe study would be women who work at as simple random sampling, have been used to ensure thathome, and women who worked outside may not be feasible where every individual who meetsthe home would be less likely to be inter- there is little information avail- certain eligibility criteria hasviewed. Since women working outside the able on the population under an equal probability of beinghome may have different experiences with study. The following is a brief included in the study. A Practical Guide for Researchers and Activists 107

CHAPTER SEVEN description of the more common sampling selection of any one individual in no way techniques used. influences the selection of any other. The Many people underestimate the chal- word “simple” does not mean that this lenge of obtaining a well-designed sample. method is any easier, but rather that steps Mistakes are often made due to confusion are taken to ensure that only chance influ- over the meaning of the term random ences the selection of respondents. selection. A random selection does not Random selection can be achieved using a mean that participants are simply selected lottery method, random number tables in no particular order. In fact, the tech- (found in many statistical books), or a niques for obtaining a truly random sample computer program such as Epi Info. To are quite complex, and inexperienced avoid bias, it is very important to include researchers should consult an expert in in the sampling frame only individuals who sampling before proceeding. A well are eligible to be interviewed by criteria thought-out and tested questionnaire used such as age, sex, or residence. By the same on a poorly designed sample will still ren- token, if certain individuals are left off the der meaningless results. original list due to an outdated census that Random samples are often confused does not include individuals who have with convenience or quota samples. A recently moved into the population area, convenience sample is when informants then these omissions could bias the results, are selected according to who is available, particularly if migration is the result of in no particular order. In a quota sample crises such as war, natural disasters, or eco- a fixed number of informants of a certain nomic collapse. In these cases, you will type are selected. Neither strategy will need to update the sampling list. result in a random sample appropriate for survey research. Systematic sampling In random sampling, each individual or Simple random sampling household is chosen randomly. In contrast, This sampling technique involves selection systematic sampling starts at a random at random from a list of the population, point in the sampling frame, and every nth known as the sampling frame. If properly person is chosen. For example, if you conducted, it ensures that each person has want a sample of 100 women from a sam- an equal and independent chance of pling frame of 5,000 women, then you being included in the sample. would randomly select a number between Independence in this case means that the one and 50 to start off the sequence, and then select every fiftieth woman thereafter. Both random and systematic sampling require a full list of the population in order to make a selection. It is also important to know how the list itself was made, and whether individuals are placed randomly or in some kind of order. If individuals from the same household or withPHOTO BY HAFM JANSEN certain characteristics are grouped together, this may result in a biased sample in which individuals with these characteristics are either overrepresented or underrepresented. 108 Researching Violence Against Women

D E V E L O P I N G A S A M P L I N G S T R AT E G YStratified samplingStratified sampling may be used togetherwith either simple random sampling or sys-tematic sampling. This ensures that thesample is as close as possible to the studypopulation with regard to certain character-istics, such as age, sex, ethnicity, or socio-economic status. In this case, the studypopulation is classified into strata, or sub-groups, and then individuals are randomly PHOTO BY HAFM JANSENselected from each stratum. Because strati-fication involves additional effort, it onlymakes sense if the characteristic beingstratified is related to the outcome understudy. For the purpose of analysis it is eas-ier if the number of individuals selected clusters (such as villages or neighbor- A street map used forfrom each stratum is proportional to their hoods). Then a random sample of these locating households in the Japan WHO study.actual distribution in the population. (See clusters is drawn for the survey. This is theBox 7.1 on self-weighting samples.) For first stage of sampling. The second stageexample, in a sample stratified according to may involve either selecting all of the sam-urban/rural residence, the proportion of pling units (respondents, households) inrural women in the sample would be the the selected clusters, or selecting a groupsame as the proportion of rural women in of sampling units from within the clusters.the study population. Sometimes more than two stages are A weighted stratified sample may be required. Thus, one might randomlypreferable when there are some groups choose districts within a province, andwhich are proportionately small in the then randomly select villages from thepopulation, but which are relevant for the selected districts as the second stage.purpose of the study, such as individuals Individual respondents would be selectedfrom a certain geographical region or eth- from the clusters as a third stage. At eachnic group. Ensuring that these groups are stage, simple random, systematic, or strati-adequately represented might require an fied techniques might be used. It is advis-inordinately large sample size using simple able to consult a statistician if you arerandom sampling techniques. In this case, considering a multistage sampling scheme.it may be appropriate to oversample, or to The advantage of multistage sampling isselect a disproportionately large number of that a sampling frame (e.g., a list of house-respondents from this stratum. This results holds) is only needed for the selected clus-in a weighted sample that will have to be ters (villages) rather than for the wholetaken into account in the analysis process. study population. Also, the logistics will be easier because the sample is restricted toMultistage and cluster sampling the selected clusters and need not coverMultistage sampling is often used for the whole study area. An example of adrawing samples from very large popula- multistage sampling strategy in Peru istions covering a large geographical area. It described in Box 7.3.involves selecting the sample in stages, or The disadvantages of multistage sam-taking samples from samples. The popula- pling are that the sample size needs to betion is first divided into naturally occurring substantially larger than if the sample was A Practical Guide for Researchers and Activists 109

CHAPTER SEVEN BOX 7.1 SELF-WEIGHTING IN CLUSTER SAMPLES I How sure do you want to be of your conclusions? Larger sample size gener- The way in which the sample is chosen greatly influences the usefulness of the ally increases the precision of the results, resulting estimates. Suppose that there is a district with only two villages: or the confidence with which one can I Village A has 4,000 women, of which 800 (20 percent) have been abused. say that they represent a reliable meas- I Village B has 800 women, of which 40 (5 percent) have been abused. ure of the phenomena under study. The true prevalence of abuse in this district would be calculated as follows: I What are the characteristics of the Total cases of violence = (800 + 40) X 100 = 17.5 percent study population? The more variability Total number of women (4000 + 800) there is in the population, the larger the sample size needed. However, if we decided to determine the prevalence of abuse in this district based on a random sample of 100 women from each village, we would find the following: I How common is the phenomenon I 20 out of 100 women in Village A reporting abuse. under study? If any of the conditions I 5 out of 100 women in Village B reporting abuse. you want to measure in your study are Combining these two figures we would find that 25 out of the 200 women inter- very rare, for example, infant mortality viewed were abused, which would give us a prevalence of 12.5 percent. or maternal mortality, then you will need a very large sample size. What has happened here? Our sampling procedure led us to an underestimated prevalence because the num- I What is the purpose of the research? ber of informants selected from each village was not in proportion to the relative size of each village. Assuming that we knew the relative sizes of the villages, we The sample size calculation will also could perform a weighted analysis where the results from Village A would count depend on whether you simply want to five times as much as those from Village B. However, it is usually preferable to measure the prevalence of a condition obtain a self-weighting sample. One way to do this would be to select five times more respondents from Village A than Village B. Another approach is to select the in a population or whether you want to villages with probability proportional to size. This means that if you have a list of vil- measure an expected difference lages, a large village like Village A would be five times more likely to be selected between two groups. Programs such as for the sample than a village the size of Village B. After the villages were selected, Epi Info contain two different formulas you could then to select an equal number of respondents from each village. (For an example of how a self-weighting sample was obtained in Peru, see Box 7.3.) for these two different approaches. (From Morison, 2000.5) I What kind of statistical analysis will you use? This underscores the need to consider how you are going to analyze selected by simple random sampling. Also, your data from the very beginning. The it can be more complicated to get a self- sample size must be large enough to weighting sample. Another difficulty with provide for desired levels of accuracy in multistage sampling can be defining clus- estimates of prevalence, and to test for ters if the study area is, for example, a the significance of differences between large urban area. Sometimes these have different variables. already been defined for previous censuses or surveys, but otherwise they have to be I What kind of sampling strategy will created from a map or based on some be used? Commonly used sample size other criteria such as school or health cen- formulae and computer packages ter catchment areas. assume you are using simple random sampling. If you plan to use multistage How large a sample do you need? or cluster sampling, you may need to The ideal sample size for a survey depends increase your sample size to achieve the on several factors: precision you require. Consider asking a110 Researching Violence Against Women

D E V E L O P I N G A S A M P L I N G S T R AT E G Y statistician for help in deciding by how BOX 7.2 POPULATION SURVEY USING RANDOM SAMPLING much the sample size needs to be (STATCALC SAMPLE SIZE AND POWER) increased. Population Size 100,000 10,000 10,000 10,000 It is better to collect excellent data from Expected Frequency 30% 30% 20% 30%fewer respondents than to collect data of Worst Acceptable Frequency 25% 25% 15% 28%dubious validity and reliability from manyrespondents. Statistical computer packages Confidence Sample Sample Sample Sampleor mathematical formulas can be used to Level Size Size Size Sizedetermine sample size for a study. Box 7.2 80% 138 136 104 794presents a table produced by Epi Info’s 90% 227 222 170 1,244STATCALC program for ideal sample size 95% 322 313 270 1,678calculations. This program is availableonline at http://www.cdc.gov/epiinfo. 99% 554 528 407 2,583 If your proposed analysis calls for study- 99.9% 901 834 648 3,624ing particular subgroups of your sample, 99.99% 1,256 1,128 883 4,428the sample size will need to be expandedaccordingly. For example, to determine theprevalence of violence, you may need a sample size calcula- How large a sample?sample of only 300 women. But if you tions. It should alsowant to know whether the prevalence of be noted that the This is one of the most common ques-violence varies by age, education, or socio- sample size will tions asked of statisticians. A frequenteconomic group, then you will need a need to be increased but erroneous answer is “as large assample size sufficiently large to allow for if a multistage sam- possible” when it instead should be “ascomparisons among these groups. ple is being used. small as possible.” The initial calculation was made based Because these calcu- It is also important to emphasize that theon a simple random sample from a study lations can be quite amount of information that can bepopulation of 100,000 women, where it complex, inexperi- gained from a sample depends on itswas assumed that approximately 30 per- enced researchers absolute size, not upon the samplingcent of women have experienced violence are urged to consult fraction, or its size as a proportion ofand that a 10 percent margin of error with someone who the population size. It is actually truewould be acceptable (5 percent above and is knowledgeable in that 99 out of one million tells you as5 percent below). If these assumptions are survey sampling much about the 1 million as 99 out ofactually true, the table indicates that with a techniques. one thousand tells you about the onesample size of 322 women, one would To explore the thousand.obtain a 95 percent confidence interval for health consequencesthe true prevalence of 25 percent and 35 of violence with (From Persson and Wall, 2003.6)percent. Note, however, that if the esti- greater precision, andmates used for sample size calculations are to compare the occurrence of violence invery inaccurate then the required precision different sites within each country, themay not be obtained. WHO VAW study uses a multistage sam- The table also shows that differences in pling strategy aiming for 3,000 interviewsthe size of the study population do not in two sites; 1,500 in the capital city andgreatly influence sample size, whereas 1,500 in a province. However, to end upchanges in the expected frequency and with 1,500 completed interviews, it is usu-particularly the level of precision that is ally necessary to increase the estimatedneeded can have an enormous effect on sample size by 10-20 percent to account A Practical Guide for Researchers and Activists 111

Mandatory reading

by Víctor Barragán

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