Overview of MMRM

Greetings--

Below is a brief overview of quantitative research. In this class, we'll cover three major quantitative methodologies-- 1) surveys, 2) experiments, and 3) content analysis, and the three major qualitative methods-- 1) interviews, 2) focus groups, 3) participant-observation.

When it comes to social science, there are two approaches-- qualitative and quantitative. While both approaches use the scientific method, a qualitative researcher believes that humans and their behaviors are far too "messy" and complex to quantify and that it is silly to even try. Instead, qualitative researchers believe that any understanding of the human condition is best ascertained by talking to people and searching for identifiable patterns among their comments.

A quantitative researcher, by comparison, believes that if a concept exists, then it  can be measured, and, conversely, if it can't be measured, then it doesn't exist.

For example, if we were to take the concept of "romantic love," an abstract concept to be sure, a quantitative researcher would say that if "love" is real and exists, then it can be measured. He/she might begin by identifying indicators of romantic love and they might include items like--

amount of time spent with the other person
level of affection
level of emotional connection
level of desire to spend time with the other person
phsyiological responses when with the other person
willingness to do things for the other person
level of communication with the other person (talking in person, snapchat, via cell, texting, email, IMing, facebook, skype, etc.)
sexual relationship
level of commitment
and so on...

The point is this- a quantitative researcher might be able to say "If I discover that a person has a high level of affection for someone, feels emotionally connected, wants to spend a lot of time with that person, experiences physiological symptoms when in the presence of the other person (heart rate increase, general feelings of happiness, goose bumps, etc.), wants to do things for that person, spends a lot of time communicating with him/her, has a healthy sexual relationship with him/her, and is committed for the long haul, and so on, then that person is 'in love.'"

Get it?

If there's one thing I want you to get out of this class, it's this-- quantitative research is practical and is a wonderful tool we have to answer some of life's most interesting questions.

So let's begin by taking a quick look at an overview of the quantitative approach:

Quantitative research overview

Quantitative research usually is designed to produce estimates of the prevalence of knowledge, attitudes, opinions, behaviors, and other characteristics of a defined population group, whether the U.S. population as a whole or some subgroup. Most quantitative research attempts to do this by using various approaches to randomly selecting a representative sample of the audience of interest, such as random household surveys, random digit-dialing telephone methodologies, or random selection of names from voter lists or other lists believed to be inclusive of all members of the audience (for example, membership lists, motor vehicle registrations, school enrollment lists).

These and other approaches can involve complex decisions about the comprehensiveness of the data from which to sample, whether the sampling should be "stratified" (a process in which attempts are made to represent different segments of the overall population of interest, such as by gender, age group, or household income), whether adequate numbers of people can be sampled from which to reliably make population estimates, as well as specific ways in which "random selection" is actually accomplished.

After a representative sample is selected, surveys are then administered to the sample via one or more modalities, including in-person, telephone, or mail, and, more recently, the Internet. Each of these methods presents technical challenges, among them ensuring that all members of the sample have equal access to the chosen modality so as to not introduce a sampling bias. Another major challenge is to achieve high response rates, so that the results are not potentially biased by unknown characteristics of either the "responders" or "nonresponders."

Because of the nature of this research, and its use of relatively high numbers of respondents, surveys often use a limited number of questions that are presented in a consistent way to all respondents. Approaches to questionnaire development and phrasing can vary in rigor from internal professional review and discussion to formal cognitive laboratory testing with potential respondents.

To facilitate data entry and analysis, most questions will be structured in a "closed-ended" format, which limits the respondents to making a choice between two or more predetermined alternative responses. "Open-ended" formats also can be used in this research. If responses given by respondents do not fall within a limited number of categories or themes that can be discerned by either software or analysis by the researcher, however, they can limit the value and generalizability of the findings.

Finally, the other defining feature of quantitative research is the statistical analysis of the responses and reporting of these data in summary form. Statistical analysis can range from simple frequencies, percentages, and cross-tabulations for selected subgroups (such as age group, income, race/ethnicity) to complex analyses that may try to explain how various characteristics of the population or subgroups relate to one another (for example, what characteristics explain differences between people who engage in a healthy behavior versus those who do not).

The results of these analyses are then used to draw conclusions about the prevalence of the measured characteristics in the larger population of interest. These results are often expressed using confidence intervals or p-values to gauge the level of certainty that the reported results may in fact reflect the population as a whole.
Benefits of quantitative research

The most important benefit of well-designed and well-implemented quantitative research is that it can give planners of communications programs fairly reliable information about the prevalence of certain characteristics among their audience. Quantitative research that is conducted on a periodic basis also can track the effects of the program on targeted knowledge, attitudes, and/or behavioral change objectives. Quantitative methods also can be used to determine if the results of qualitative research are valid for the larger population.
Limitations of quantitative research

Researchers must consider several limitations of quantitative research before making a decision to conduct audience research using this family of approaches. The more important limitations are:

* Such approaches usually are resource intensive and can take several weeks to many months to design, implement, and analyze, thus extending the time needed to incorporate audience-based research into program planning. One option to address this limitation is to add questions to ongoing omnibus marketing and opinion-sampling surveys conducted by commercial entities. These results can be turned around much more quickly. How these firms construct their samples, what modalities they use for interviewing, and how they achieve high response rates all need to be explored, however, to assure the quality of the information provided to the planners.

* Quantitative research also requires skills in sampling design issues, sampling methodologies, survey design, statistical techniques, and how they are all applied in a communications research context. The extent to which these skills are used in planning and carrying out a quantitative study determines both the quality of the data and their generalizability to the total population.

* The structure of most surveys limits the number of questions that can be asked, the variety of responses that respondents can provide, the time each respondent has to answer questions (15–20 minutes is what many surveys aim for to minimize respondent burden and to maximize full completion of the survey), and any type of interactive process with or among respondents. Thus the data are limited in the amount and richness of audience information that can be fed into the program and message design processes.