The two research variables under analysis are sampling and measurement instruments. These variables pose serious problems for cross-cultural researchers owing to differences that stem from the subjects, administrators as well as the material in question.
One of the key challenges in sampling within multicultural research methodology is the problem of clearly defining a representative group. For instance, some researchers may want to apply their research across a series of cultures. Selecting nation states as representatives for certain cultures, such as China, India and South Africa, may not be accurate (Kankaras & Moors, 2010).
This is true because many nations consist of heterogeneous cultures; therefore, a young accountant in Beijing may have different opinions from one in the rural village of Guangzhou. One way of correcting this misrepresentation is to use cult-units. These are people who speak the same language, live in the same territory and are governed by similar political authorities.
Additionally, the chosen sample must also relate to theoretical considerations. Many times, cross-cultural researchers may select samples on the basis of convenience rather than the objectives of the study. In this regard, choosing two cultures may not be sufficient for a cross-cultural analysis. One must consider the usefulness of the analysis in relation to theory.
Relevance of one’s research objectives also comes into play when implementing measurement instruments. Differential item functioning can arise when subjects with similar qualities, such as intelligence, will score differently in a test due to cultural differences. A case in point was an international study designed to analyze educational achievement.
Respondents were required to identify the habitat of a bird with swimming feet. It was found that Swedish subjects scored highly in this test item. Later, the administrators realized that the Swedish translation for the question gave clues on the answer. In another analysis on intelligence, high school students from Austria, Togo and Nigeria did an inductive-analysis test.
It was found that the Togolese students scored poorly despite the fact that other intelligence tests gave them equal rankings to Nigeria. The test was arranged in a way that required left to right movement, yet this was unnatural for Arabic speakers like the Togolese. Therefore, the research was biased in favor of Anglophone cultures (Malhotra et. al.,1996).
Defining the right target population is also a challenge in cross-cultural research. For instance, if a person was analyzing the psychology of children’s cereals purchases, they would have to consider children as the key sampling element in western cultures, like the US. However, if they studied the same concept in regions with authoritarian parenting practices, then mothers would be the main sampling elements.
On the other hand, in male-dominated cultures, the sampling element would be the father. In the Middle East, it is common practice for fathers to purchase all household goods. A researcher doing multi-cultural research in the US, Nigeria and Saudi Arabia on children’s cereals would have to interview a child, mother and father, respectively.
Similarly, differences in target’s behavior may also manifest when implementing measurement instruments. However, in this research variable, the problem is usually on the part of the research administrator. In multi-cultural analyses, it has been shown that subjects are more likely to demonstrate positive attitudes to a person from their group.
However, in heterogeneous cultures, it may be difficult to find a person with a multiplicity of traits. Furthermore, challenges can arise when communicating. If the research administrator has language deficiencies in one culture and fluency in another, then the interviewer may bias the results.
Challenges in making a sampling frame may inhibit the success of multi-cultural research methodology. Some nations lack demographic information concerning their populations. For instance, census reports may not consider servants or women. Therefore, developing the right sampling frame may be difficult. In countries like Mexico, strangers are not allowed inside one’s residence.
Researchers can find it difficult to obtain information about the residents. Government data may be biased or unavailable. For instance, some monarchies do not conduct elections, so voter registration records may be nonexistent. Even finding maps for representative population may be a tall order.
Issues of accessibility may be quite difficult in implementing a sampling strategy. Some cultures may discourage women from interacting with strangers or members of the opposite sex. Therefore, interviewers may not access these individuals, yet they may be a critical part of the research objectives. One may be stuck with respondents who do not represent the desired target population.
Similar problems of accessibility can also be encountered when dealing with measurement instruments. Physical conditions have a direct effect on the results reported in a survey. For instance, if a person selected an unstructured questionnaire as the measuring instrument, then an interviewer will need to collect the information physically.
If the respondent’s setting is noisy or disruptive, then dissimilar results will be obtained. Additionally, personal questions may be easily answered in anonymous questionnaires than the intrusive setting of a personal interview. The degree to which questions may be perceived as personal is dependent on one’s culture (Olatundun, 2009).
Problems of estimating the right sample size can also manifest in cross-cultural analyses. If a culture is homogenous, it requires a relatively small sample size. However, heterogeneous cultures require large representatives. Researchers may find it difficult to estimate the right number needed to portray these qualities.
In order to diffuse this problem, researchers ought to combine a range of sampling techniques in response to their chosen demographic. Sometimes judgmental sampling may be necessary. In this regard, they need to know the characteristics of the target population and how they are likely to respond to certain questions.
Thorough knowledge of the target population in multicultural implementation of measurement instruments may also be necessary in order to minimize biases in responses. Stimulus familiarity is one of the problems in carrying out tests in several cultures. Measurement instruments must be such that they do not contain information which some cultures are familiar with and others are not.
This problem was determined in one of the most commonly cited researches in psychology; a study of feeblemindedness among immigrant populations in the US (Gjersing et. al., 2010). The administrators used a measurement instrument that was familiar to indigenous Americans.
However, the same was not true for the immigrant population, which appeared less intelligent than their counterparts. Therefore, research administrators must design instruments that do not lead to stimulus familiarity in one culture over the other. This requires through knowledge of the groups to be analyzed.
In conclusion, the research variables each have their own set of biases in cross cultural analysis. However, these biases stem from misrepresentation of the true constructs. Sometimes the qualities of the cultural groups may lead to misrepresentation or the research administrator may be the source of bias.
Gjersing, L., Caplehorn, J. & Clausen, T. (2010). Cross cultural adaptation of research instruments. BMC Medical Research Methodology, 10(13), 2-10.
Kankaras, M. & Moors, G. (2010). Research measurement equivalence in cross cultural studies. Psihologija, 43(2), 122-125
Malhotra, N., Agarwal, J., Peterson, M. (1996). Methodological issues in cross cultural marketing research. International marketing review, 13(5), 7-43.
Olatundun, O. (2009). What is cross cultural research, International Journal of psychological Studies, 1(2), 122-125.