Skip to main content

Costs of Paradata... Analysis

One of the hidden costs of paradata are the time spent analyzing these data. Here, we've spent a lot of time trying to find standard ways to convert these data into useful information. But many times, we end up doing specialized analyses. Searching for an explanation of some issue. And, sometimes, this analysis doesn't lead to clear-cut answers.

In any event, paradata aren't just collected, they are also managed and analyzed. So there are costs for generating information from these data. We could probably think of this in a total survey error perspective. "Does this analysis reduce total error more than increasing the number of interviews?" In practice, such a question is difficult to answer. What is the value of the analysis we never did? And how much would it have cost?

There might be two extreme policies in this regard. One is "paralysis by analysis." Continually seeking information and delaying decisions. The other extreme is "flying by the seat of the pants," making uninformed decisions frequently. Most of the time, we choose a policy somewhere between these two extremes and hope that we made a nearly optimal choice.

Perhaps the whole problem goes away as we become more adept at manipulating large, complicated data structures. Maybe. I can at least say that hasn't happened yet.

Comments

  1. From starting to finish a survey takes lot of time. However, after a survey using the collected information wisely is challenging. It's good to learn how this thing can be done after a successful survey or, you can try PanXpan (an analytics software) that has a Survey Response Analysis module which can help with this. It's a cost effective software. It's free to try and after that only costs $10 a month.

    ReplyDelete

Post a Comment

Popular posts from this blog

"Responsive Design" and "Adaptive Design"

My dissertation was entitled "Adaptive Survey Design to Reduce Nonresponse Bias." I had been working for several years on "responsive designs" before that. As I was preparing my dissertation, I really saw "adaptive" design as a subset of responsive design.

Since then, I've seen both terms used in different places. As both terms are relatively new, there is likely to be confusion about the meanings. I thought I might offer my understanding of the terms, for what it's worth.

The term "responsive design" was developed by Groves and Heeringa (2006). They coined the term, so I think their definition is the one that should be used. They defined "responsive design" in the following way:

1. Preidentify a set of design features that affect cost and error tradeoffs.
2. Identify indicators for these costs and errors. Monitor these during data collection.
3. Alter the design features based on pre-identified decision rules based on the indi…

An Experimental Adaptive Contact Strategy

I'm running an experiment on contact methods in a telephone survey. I'm going to present the results of the experiment at the FCSM conference in November. Here's the basic idea.

Multi-level models are fit daily with the household being a grouping factor. The models provide household-specific estimates of the probability of contact for each of four call windows. The predictor variables in this model are the geographic context variables available for an RDD sample.

Let $\mathbf{X_{ij}}$ denote a $k_j \times 1$ vector of demographic variables for the $i^{th}$ person and $j^{th}$ call. The data records are calls. There may be zero, one, or multiple calls to household in each window. The outcome variable is an indicator for whether contact was achieved on the call. This contact indicator is denoted $R_{ijl}$ for the $i^{th}$ person on the $j^{th}$ call to the $l^{th}$ window. Then for each of the four call windows denoted $l$, a separate model is fit where each household is assum…

Is there such a thing as "mode"?

Ok. The title is a provocative question. But it's one that I've been thinking about recently. A few years ago, I was working on a lit review for a mixed-mode experiment that we had done. I found that the results were inconsistent on an important aspect of mixed-mode studies -- the sequence of modes.

As I was puzzled about this, I went back and tried to write down more information about the design of each of the experiments that I was reviewing. I started to notice a pattern. Many mixed-mode surveys offered "more" of the first mode. For example, in a web-mail study, there might be 3 mailings with the mail survey and one mailed request for a web survey. This led me to think of "dosage" as an important attribute of mixed-mode surveys.

I'm starting to think there is much more to it than that. The context matters  a lot -- the dosage of the mode, what it may require to complete that mode, the survey population, etc. All of these things matter.

Still, we ofte…