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6

It's important to distinguish between measures and analyses, because only analyses can be quantitative or qualitative, not measures. Measures are, essentially, systematic processes by which we acquire our data, and analyses are processes we use to look at the data. As a rule of thumb, the difference is not hard to find and is given in the name: ...


5

ANOVA and t-tests are statistical tests for significance and therefore quantitative. The other mentioned items are scales (adding numbers to a certain choice) and therefore they can be considered as ordinal scales, and hence as quantitative as they are based on numbers. The NASA one can be administered by using a sliding scale which can be considered to ...


2

The R package diffIRT (http://www.dylanmolenaar.nl/jss1265.pdf) estimates both the Q and the D diffusion models (see his website for the van der Maas et al. paper discussing the differences between these models). R code for the EZ2 approach, which is much faster if that is important for your applications, is http://raoul.socsci.uva.nl/EZ2/.


4

It depends on the types of changes you are looking to make. In general, my experience has been that changes to a response scale can be done with minimal threats to validity (e.g. looking to change the 4 item Likert type scale to a 6 item Likert type scale). On the other hand, changing question wording itself usually can't be done "without losing validity" ...


2

Short answer: The data is likely to be noisier, the absolute reaction time can't be trusted, but given enough power (which is easy to obtain on the Internet) relative reaction time differences should be similar to those in the lab. However, web-based reaction time studies might pose other problems, because you have less control over stimulus presentation and ...


3

There are a few factors that could contribute to differences between online versus in-lab reaction time measurement. Hardware variation Participants in an online experiment will use their own computers to complete the task, which will result in lots of variation in hardware. Many studies have looked at how hardware variations affect response time ...


1

Depending on how you collect the data, reaction times collected "online" will likely be different from those collected "on-site". When considering reaction times, it is important to decide if the reaction time is being used as a trigger, as the time to a response, or the difference in the time to response. Consider an experiment which displays a random ...


2

The main threat to a design's validity from increasing the amount of trials in any experiment comes from participant motivation and attention. After sitting in front of a monitor for a while, participants get tired, as anyone would. As a personal rule of thumb, a session should therefore not go beyond 40 minutes without breaks if possible. Rather than going ...



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