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188
submitted). Mixedeffects modeling with crossed random effects for subjects and items
, 2007
"... and items ..."
Categorical Data Analysis: Away from ANOVAs (transformation or not) and towards Logit Mixed Models
"... This paper identifies several serious problems with the widespread use of ANOVAs for the analysis of categorical outcome variables such as forcedchoice variables, questionanswer accuracy, choice in production (e.g. in syntactic priming research), et cetera. I show that even after applying the arc ..."
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Cited by 62 (6 self)
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This paper identifies several serious problems with the widespread use of ANOVAs for the analysis of categorical outcome variables such as forcedchoice variables, questionanswer accuracy, choice in production (e.g. in syntactic priming research), et cetera. I show that even after applying the arcsinesquareroot transformation to proportional data, ANOVA can yield spurious results. I discuss conceptual issues underlying these problems and alternatives provided by modern statistics. Specifically, I introduce ordinary logit models (i.e. logistic regression), which are wellsuited to analyze categorical data and offer many advantages over ANOVA. Unfortunately, ordinary logit models do not include random effect modeling. To address this issue, I describe mixed logit models (Generalized Linear Mixed Models for binomially distributed outcomes, Breslow & Clayton, 1993), which combine the advantages of ordinary logit models with the ability to account for random subject and item effects in one step of analysis. Throughout the paper, I use a psycholinguistic data set to compare the different statistical methods.
Simultaneous Inference in General Parametric Models
, 2008
"... Simultaneous inference is a common problem in many areas of application. If multiple null hypotheses are tested simultaneously, the probability of rejecting erroneously at least one of them increases beyond the prespecified significance level. Simultaneous inference procedures have to be used which ..."
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Cited by 23 (3 self)
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Simultaneous inference is a common problem in many areas of application. If multiple null hypotheses are tested simultaneously, the probability of rejecting erroneously at least one of them increases beyond the prespecified significance level. Simultaneous inference procedures have to be used which adjust for multiplicity and thus control the overall type I error rate. In this paper we describe simultaneous inference procedures in general parametric models, where the experimental questions are specified through a linear combination of elemental model parameters. The framework described here is quite general and extends the canonical theory of multiple comparison procedures in ANOVA models to linear regression problems, generalized linear models, linear mixed effects models, the Cox model, robust linear models, etc. Several examples using a variety of different statistical models illustrate the breadth of the results. For the analyses we use the R addon package multcomp, which provides a convenient interface to the general approach adopted here. Key words: multiple tests, multiple comparisons, simultaneous confidence intervals, adjusted pvalues, multivariate normal distribution, robust statistics. 1
Parsing costs as predictors of reading difficulty: An evaluation using the Potsdam Sentence Corpus
 Journal of Eye Movement Research
, 2008
"... The surprisal of a word on a probabilistic grammar constitutes a promising complexity metric for human sentence comprehension difficulty. Using two different grammar types, surprisal is shown to have an effect on fixation durations and regression probabilities in a sample of German readers ’ eye mov ..."
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Cited by 22 (5 self)
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The surprisal of a word on a probabilistic grammar constitutes a promising complexity metric for human sentence comprehension difficulty. Using two different grammar types, surprisal is shown to have an effect on fixation durations and regression probabilities in a sample of German readers ’ eye movements, the Potsdam Sentence Corpus. A linear mixedeffects model was used to quantify the effect of surprisal while taking into account unigram frequency and bigram frequency (transitional probability), word length, and empiricallyderived word predictability; the socalled “early ” and “late ” measures of processing difficulty both showed an effect of surprisal. Surprisal is also shown to have a small but statistically nonsignificant effect on empiricallyderived predictability itself. This work thus demonstrates the importance of including parsing costs as a predictor of comprehension difficulty in models of reading, and suggests that a simple identification of syntactic parsing costs with early measures and late measures with durations of postsyntactic events may be difficult to uphold.
Analyzing ‘visual world ’ eyetracking data using multilevel logistic regression
"... NOTICE: this is the author’s version of a work that was accepted for publication in Journal of Memory and Language. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this docum ..."
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Cited by 17 (0 self)
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NOTICE: this is the author’s version of a work that was accepted for publication in Journal of Memory and Language. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A new framework is offered that uses multilevel logistic regression (MLR) to analyze data from ‘visual world ’ eyetracking experiments used in psycholinguistic research. The MLR framework overcomes some of the problems using conventional analyses, making it possible to incorporate time as a continuous variable and gaze location as a categorical dependent variable. The multilevel approach minimizes the need for data aggregation and thus provides a more statistically powerful approach. With MLR, the researcher builds a mathematical model of the overall response curve that separates the response into different temporal components. The researcher can test hypotheses by examining the impact of independent variables and their interactions on these components. A worked example using MLR is provided. The current article provides solutions for the analysis of data sets from eyetracking experiments that use the ‘visual world’
Panel Data Econometrics in R: The plm Package
 Journal of Statistical Software
, 2008
"... This introduction to the plm package is a slightly modified version of Croissant and Millo (2008), published in the Journal of Statistical Software. Panel data econometrics is obviously one of the main fields in the profession, but most of the models used are difficult to estimate with R. plm is a p ..."
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Cited by 13 (1 self)
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This introduction to the plm package is a slightly modified version of Croissant and Millo (2008), published in the Journal of Statistical Software. Panel data econometrics is obviously one of the main fields in the profession, but most of the models used are difficult to estimate with R. plm is a package for R which intends to make the estimation of linear panel models straightforward. plm provides functions to estimate a wide variety of models and to make (robust) inference. Keywords:˜panel data, covariance matrix estimators, generalized method of moments, R. 1.
Optimal Processing Times in Reading: a Formal Model and Empirical Investigation
"... It is widely known that humans can respond to events they expect more quickly than to unexpected events, but we still have a poor understanding of why. Models exist that derive a relation between subjective probability and response time on the basis of optimal perceptual discrimination, but these mo ..."
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Cited by 11 (2 self)
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It is widely known that humans can respond to events they expect more quickly than to unexpected events, but we still have a poor understanding of why. Models exist that derive a relation between subjective probability and response time on the basis of optimal perceptual discrimination, but these models rely on the ability of the responder control over perceptual sampling of the environment, rendering them problematic for some domains, such as auditory language processing, in which there are nevertheless clear dependencies between probability and response time. We present a new model deriving the relationship between probability and reaction time as a consequence of optimal preparation. This model is valid under very general conditions, requiring only that the results of optimization are invariant across scale of input stimulus granularity. The model makes the strong prediction that response times should scale linearly with the negative conditional logprobability of the stimulus. We present evidence for this prediction in an analysis of an existing database of eye movements in the reading of naturalistic texts.
Implicit learning and syntactic persistence: surprisal and cumulativity
, 2008
"... to repeat a syntactic structure that they have processed previously. In the following example (1) from the Switchboard corpus (Godfrey et al., 1992), the speaker produces the double object ditransitive structure, or NPNP (1a), as opposed to the prepositional object structure, or NPPP (1b), after h ..."
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Cited by 8 (1 self)
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to repeat a syntactic structure that they have processed previously. In the following example (1) from the Switchboard corpus (Godfrey et al., 1992), the speaker produces the double object ditransitive structure, or NPNP (1a), as opposed to the prepositional object structure, or NPPP (1b), after having produced an NPNP previously in the conversation: (1) “... I don’t feel we should loan [them] [money]... I wish our leaders were really seeking the Lord on these things, and if we feel led to give [a country] [money] to help them, fine” a. (NPNP) give [a country] [money] b. (NPPP) give [money] [to a country] In other words, syntactic persistence in production refers to the phenomenon that a structure’s posteriori probability of occurring is increased – compared to its a priori probability of occurring – after another instance of the same structure. As such, syntactic persistence is an empirical fact (Bock, 1986; Pickering and Branigan, 1998, inter alia). Relatively little is known, however, about the underlying mechanisms that cause syntactic persistence. In this paper, we ask why syntactic persistence exists. We aim to distinguish between two prominent theories about the underlying causes of persistence.
Evaluating Speech Synthesis Intelligibility using Amazon Mechanical Turk
, 2010
"... Microtask platforms such as Amazon Mechanical Turk (AMT) are increasingly used to create speech and language resources. AMT in particular allows researchers to quickly recruit a large number of fairly demographically diverse participants. In this study, we investigated whether AMT can be used for co ..."
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Cited by 5 (0 self)
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Microtask platforms such as Amazon Mechanical Turk (AMT) are increasingly used to create speech and language resources. AMT in particular allows researchers to quickly recruit a large number of fairly demographically diverse participants. In this study, we investigated whether AMT can be used for comparing the intelligibility of speech synthesis systems. We conducted two experiments in the lab and via AMT, one comparing US English diphone to US English speakeradaptive HTS synthesis and one comparing UK English unit selection to UK English speakerdependent HTS synthesis. While AMT word error rates were worse than lab error rates, AMT results were more sensitive to relative differences between systems. This is mainly due to the larger number of listeners. Boxplots and multilevel modelling allowed us to identify listeners who performed particularly badly, while thresholding was sufficient to eliminate rogue workers. We conclude that AMT is a viable platform for synthetic speech intelligibility comparisons.
Parallel processing and sentence comprehension difficulty
, 2010
"... Eye fixation durations during normal reading correlate with processing difficulty but the specific cognitive mechanisms reflected in these measures are not well understood. This study finds support in German readers’ eye fixations for two distinct difficulty metrics: surprisal, which reflects the ch ..."
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Cited by 5 (1 self)
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Eye fixation durations during normal reading correlate with processing difficulty but the specific cognitive mechanisms reflected in these measures are not well understood. This study finds support in German readers’ eye fixations for two distinct difficulty metrics: surprisal, which reflects the change in probabilities across syntactic analyses as new words are integrated, and retrieval, which quantifies comprehension difficulty in terms of working memory constraints. We examine the predictions of both metrics using a family of dependency parsers indexed by an upper limit on the number of candidate syntactic analyses they retain at successive words. Surprisal models all fixation measures and regression probability. By contrast, retrieval does not model any measure in serial processing. As more candidate analyses are considered in parallel at each word, retrieval can account for the same measures as surprisal. This pattern suggests an important role for ranked parallelism in theories of sentence comprehension.