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Addressing the "Language as fixed effect fallacy" (F1-F2) debate with advanced regression models: A user-friendly tutorial on using Hierarchical Linear Modeling in SPSS to combine by-subjects and by-items analyses.
(Presented
May 02 2008)
Powerpoint and related files to appear.
There have been calls in the literature to analyze data in the typical
manner by subjects (i.e., computing condition means for each
participant, averaging across all items) but also by items (i.e.,
computing condition means for each item averaged across all subjects),
which are referred to as F1 and F2 analyses, respectively. Finding a
significant effect in both the F1 and the F2 analyses (i.e., the F1 x
F2 approach) or in the more conservative min F prime calculation
(which integrates F1 and F2 values into one inferential statistic) has
been (mis)interpreted as suggesting the effect "generalizes across
participants and items." After briefly reviewing the need for and
implentation of the F1 x F2 and min F prime analytic approaches using
ANOVAs, I will discuss some recent criticisms of these
approaches. Then, I will provide a brief tutorial on using an advanced
regression technique known as Hierarchical Linear Modeling or Mixed
Level Modeling that provides a more powerful analysis while also
addressing these concerns. To illustrate the usefulness and ease of
implementation of this regression technique, I will present analyses
of Translation Recognition RT data from our lab and compare the
results of the typical ANOVA models with the results of these
regression models. Time permitting, I plan to walk through in detail
how to interpret the output from these regression models so others can
begin using this analytic technique in their own research.
Bi-directional talker-listener adaptation in speech communication
(Presented
Apr. 11 2008)
Powerpoint to appear.
"Speech communication involves a chain of events that ideally aligns
mental representations in the talker with those in the listener.
Links in the chain can be "broken" at many points, particularly in
cases where the talker and listener approach each other with
non-optimally aligned linguistic sound systems (e.g. when they do not
come from the same native language background) or when the listener's
access to the speech signal may be blocked by a hearing impairment or
the presence of background noise. I will present a series of studies
that aimed to understand how talkers and listeners repair these
breakdowns in order to achieve talker-listener alignment. The first
study examined talker adaptation to the listener. Specifically, we
conducted a series of acoustic-phonetic comparisons of "clear speech"
across languages with various phonological structures. A second study
focused on the other side of the talker-listener channel by examining
listener adaptation to the talker. In particular, we investigated
listener adaptation to foreign-accented speech. Both of these studies
examined talker-listener adaptation under laboratory conditions in
which the talker and listener did not interact directly. A third
study examined talker-listener interactions under more natural
conditions of spontaneous, dialogue recordings. In this study we
examined communicative efficiency and phonetic convergence in English
conversations between pairs of native English talkers and in
conversations between one native and one non-native talker of English.
Together, these studies build a picture of speech communication as a
bidirectional process of talker-listener alignment even in the case of
communication between interlocutors who do not share a "mother
tongue."
Using hierarchical regression analyses in psycholinguistic investigations: A mini-tutorial
(Presented
Apr. 8 2008)
The slides from the workshop, along with the
SPSS data file and output file, and the Excel spreadsheet (with a ReadMe) are attached here.
Experimental
Design on a Dime by Jared Linck
(Presented
Dec. 14 2007)
You can obtain the mix and match programs and example files here or on the CLS Angel Page.
"In this presentation, I will present
two computer programs that can be extremely helpful when preparing
stimuli for an experiment. The MATCH program can be used to match
stimuli on any number of dimensions ( e.g., word frequency, word
length, reaction times). The MIX program can be used to create
randomly or pseudorandomly mixed stimulus lists. This program is
particularly useful when certain constraints need to be set for
the ordering of stimuli."