Example of Journal of Memory and Language format
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Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format
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Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format Example of Journal of Memory and Language format
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open access Open Access
recommended Recommended

Journal of Memory and Language — Template for authors

Publisher: Elsevier
Categories Rank Trend in last 3 yrs
Language and Linguistics #6 of 879 up up by 7 ranks
Linguistics and Language #7 of 935 up up by 9 ranks
Experimental and Cognitive Psychology #9 of 148 up up by 16 ranks
Neuropsychology and Physiological Psychology #4 of 60 up up by 11 ranks
Artificial Intelligence #41 of 227 down down by 1 rank
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 278 Published Papers | 2137 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 16/06/2020
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Related Journals

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recommended Recommended

Elsevier

Quality:  
High
CiteRatio: 5.7
SJR: 2.223
SNIP: 2.098
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Cambridge University Press

Quality:  
High
CiteRatio: 2.5
SJR: 0.988
SNIP: 1.054
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Cambridge University Press

Quality:  
High
CiteRatio: 3.2
SJR: 1.063
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open access Open Access
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Cambridge University Press

Quality:  
High
CiteRatio: 3.8
SJR: 0.29
SNIP: 1.153

Journal Performance & Insights

Impact Factor

CiteRatio

Determines the importance of a journal by taking a measure of frequency with which the average article in a journal has been cited in a particular year.

A measure of average citations received per peer-reviewed paper published in the journal.

3.893

1% from 2018

Impact factor for Journal of Memory and Language from 2016 - 2019
Year Value
2019 3.893
2018 3.858
2017 2.829
2016 3.065
graph view Graph view
table view Table view

7.7

13% from 2019

CiteRatio for Journal of Memory and Language from 2016 - 2020
Year Value
2020 7.7
2019 6.8
2018 5.7
2017 5.0
2016 9.5
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has increased by 1% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • CiteRatio of this journal has increased by 13% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

2.442

21% from 2019

SJR for Journal of Memory and Language from 2016 - 2020
Year Value
2020 2.442
2019 3.093
2018 3.007
2017 1.893
2016 4.102
graph view Graph view
table view Table view

2.279

4% from 2019

SNIP for Journal of Memory and Language from 2016 - 2020
Year Value
2020 2.279
2019 2.189
2018 1.923
2017 1.696
2016 2.961
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has decreased by 21% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has increased by 4% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Journal of Memory and Language

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Elsevier

Journal of Memory and Language

Articles in the Journal of Memory and Language contribute to the formulation of scientific issues and theories in the areas of memory, language comprehension and production, and cognitive processes. Special emphasis is given to research articles that provide new theoretical in...... Read More

Language and Linguistics

Linguistics and Language

Experimental and Cognitive Psychology

Artificial Intelligence

Neuropsychology and Physiological Psychology

Arts and Humanities

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Last updated on
15 Jun 2020
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ISSN
0749-596X
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Impact Factor
High - 2.101
i
Open Access
No
i
Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
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Endnote Style
Download Available
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Bibliography Name
elsarticle-num
i
Citation Type
Numbered
[25]
i
Bibliography Example
G. E. Blonder, M. Tinkham, T. M. Klapwijk, Transition from metallic to tunneling regimes in superconducting microconstrictions: Excess current, charge imbalance, and supercurrent conversion, Phys. Rev. B 25 (7) (1982) 4515–4532. URL 10.1103/PhysRevB.25.4515

Top papers written in this journal

open accessOpen access Journal Article DOI: 10.1016/J.JML.2007.12.005
Mixed-effects modeling with crossed random effects for subjects and items
R.H. Baayen1, Douglas J. Davidson2, Douglas M. Bates3

Abstract:

This paper provides an introduction to mixed-effects models for the analysis of repeated measurement data with subjects and items as crossed random effects. A worked-out example of how to use recent software for mixed-effects modeling is provided. Simulation studies illustrate the advantages offered by mixed-effects analyses ... This paper provides an introduction to mixed-effects models for the analysis of repeated measurement data with subjects and items as crossed random effects. A worked-out example of how to use recent software for mixed-effects modeling is provided. Simulation studies illustrate the advantages offered by mixed-effects analyses compared to traditional analyses based on quasi-F tests, by-subjects analyses, combined by-subjects and by-items analyses, and random regression. Applications and possibilities across a range of domains of inquiry are discussed. read more read less

Topics:

Random effects model (55%)55% related to the paper
View PDF
6,021 Citations
open accessOpen access Journal Article DOI: 10.1016/J.JML.2012.11.001
Random effects structure for confirmatory hypothesis testing: Keep it maximal
Dale J. Barr1, Roger Levy2, Christoph Scheepers1, Harry Tily

Abstract:

Linear mixed-effects models (LMEMs) have become increasingly prominent in psycholinguistics and related areas. However, many researchers do not seem to appreciate how random effects structures affect the generalizability of an analysis. Here, we argue that researchers using LMEMs for confirmatory hypothesis testing should min... Linear mixed-effects models (LMEMs) have become increasingly prominent in psycholinguistics and related areas. However, many researchers do not seem to appreciate how random effects structures affect the generalizability of an analysis. Here, we argue that researchers using LMEMs for confirmatory hypothesis testing should minimally adhere to the standards that have been in place for many decades. Through theoretical arguments and Monte Carlo simulation, we show that LMEMs generalize best when they include the maximal random effects structure justified by the design. The generalization performance of LMEMs including data-driven random effects structures strongly depends upon modeling criteria and sample size, yielding reasonable results on moderately-sized samples when conservative criteria are used, but with little or no power advantage over maximal models. Finally, random-intercepts-only LMEMs used on within-subjects and/or within-items data from populations where subjects and/or items vary in their sensitivity to experimental manipulations always generalize worse than separate F1 and F2 tests, and in many cases, even worse than F1 alone. Maximal LMEMs should be the ‘gold standard’ for confirmatory hypothesis testing in psycholinguistics and beyond. read more read less

Topics:

Random effects model (53%)53% related to the paper, Statistical hypothesis testing (53%)53% related to the paper
View PDF
5,453 Citations
Journal Article DOI: 10.1016/0749-596X(91)90025-F
A process dissociation framework: Separating automatic from intentional uses of memory
Larry L. Jacoby1

Abstract:

This paper begins by considering problems that have plagued investigations of automatic or unconscious influences of perception and memory. A process dissociation procedure that provides an escape from those problems is introduced. The process dissociation procedure separates the contributions of different types of processes ... This paper begins by considering problems that have plagued investigations of automatic or unconscious influences of perception and memory. A process dissociation procedure that provides an escape from those problems is introduced. The process dissociation procedure separates the contributions of different types of processes to performance of a task, rather than equating processes with tasks. Using that procedure, I provide new evidence in favor of a two-factor theory of recognition memory; one factor relies on automatic processes and the other relies on intentional processes. Recollection (an intentional use of memory) is hampered when attention is divided, rather than full, at the time of test. In contrast, the use of familiarity as a basis for recognition memory judgments (an automatic use of memory) is shown to be invariant across full versus divided attention, manipulated at test. Process dissociation procedures provide a general framework for separating automatic from intentional forms of processing in a variety of domains; including perception, memory, and thought. read more read less

Topics:

Implicit memory (56%)56% related to the paper, Recall (54%)54% related to the paper, Indirect tests of memory (53%)53% related to the paper, Unconscious cognition (52%)52% related to the paper, Recognition memory (50%)50% related to the paper
3,448 Citations
Journal Article DOI: 10.1006/JMLA.2002.2864
The Nature of Recollection and Familiarity: A Review of 30 Years of Research
Andrew P. Yonelinas1

Abstract:

To account for dissociations observed in recognition memory tests, several dual-process models have been proposed that assume that recognition judgments can be based on the recollection of details about previous events or on the assessment of stimulus familiarity. In the current article, these models are examined, along with ... To account for dissociations observed in recognition memory tests, several dual-process models have been proposed that assume that recognition judgments can be based on the recollection of details about previous events or on the assessment of stimulus familiarity. In the current article, these models are examined, along with the methods that have been developed to measure recollection and familiarity. The relevant empirical literature from behavioral, neuropsychological, and neuroimaging studies is then reviewed in order to assess model predictions. Results from a variety of measurement methods, including task-dissociation and process-estimation methods, are found to lead to remarkably consistent conclusions about the nature of recollection and familiarity, particularly when ceiling effects are avoided. For example, recollection is found to be more sensitive than familiarity to response speeding, division of attention, generation, semantic encoding, the effects of aging, and the amnestic effects of benzodiazepines, but it is less sensitive than familiarity to shifts in response criterion, fluency manipulations, forgetting over short retention intervals, and some perceptual manipulations. Moreover, neuropsychological and neuroimaging results indicate that the two processes rely on partially distinct neural substrates and provide support for models that assume that recollection relies on the hippocampus and prefrontal cortex, whereas familiarity relies on regions surrounding the hippocampus. Double dissociations produced by experimental manipulations at time of test indicate that the two processes are independent at retrieval, and single dissociations produced by study manipulations indicate that they are partially independent during encoding. Recollection is similar but not identical to free recall, whereas familiarity is similar to conceptual implicit memory, but is dissociable from perceptual implicit memory. Finally, the results indicate that recollection reflects a thresholdlike retrieval process that supports novel learning, whereas familiarity reflects a signal-detection process that can support novel learning only under certain conditions. The results verify a number of model predictions and prove useful in resolving several theoretical disagreements. read more read less

Topics:

Recognition memory (53%)53% related to the paper, Recall (53%)53% related to the paper, Implicit memory (52%)52% related to the paper, Forgetting (52%)52% related to the paper, Free recall (51%)51% related to the paper
3,219 Citations
open accessOpen access Journal Article DOI: 10.1016/J.JML.2007.11.007
Categorical data analysis: Away from ANOVAs (transformation or not) and towards logit mixed models
T. Florian Jaeger1

Abstract:

This paper identifies several serious problems with the widespread use of ANOVAs for the analysis of categorical outcome variables such as forced-choice variables, question-answer accuracy, choice in production (e.g. in syntactic priming research), et cetera. I show that even after applying the arcsine-square-root transformat... This paper identifies several serious problems with the widespread use of ANOVAs for the analysis of categorical outcome variables such as forced-choice variables, question-answer accuracy, choice in production (e.g. in syntactic priming research), et cetera. I show that even after applying the arcsine-square-root 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 well-suited 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 and Clayton [Breslow, N. E. & Clayton, D. G. (1993). Approximate inference in generalized linear mixed models. Journal of the American Statistical Society 88 (421), 9–25]), 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. read more read less

Topics:

Mixed logit (68%)68% related to the paper, Categorical variable (60%)60% related to the paper, Generalized linear mixed model (59%)59% related to the paper, Logit (58%)58% related to the paper, Logistic regression (57%)57% related to the paper
2,651 Citations
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Frequently asked questions

1. Can I write Journal of Memory and Language in LaTeX?

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Yes, the template is compliant with the Journal of Memory and Language guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in Journal of Memory and Language?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the Journal of Memory and Language citation style.

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Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for Journal of Memory and Language.

5. Can I use a manuscript in Journal of Memory and Language that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper Journal of Memory and Language that you can download at the end.

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7. Where can I find the template for the Journal of Memory and Language?

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11. What is the output that I would get after using Journal of Memory and Language?

After writing your paper autoformatting in Journal of Memory and Language, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is Journal of Memory and Language's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for Journal of Memory and Language?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for Journal of Memory and Language. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In Journal of Memory and Language?

The 5 most common citation types in order of usage for Journal of Memory and Language are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

15. How do I submit my article to the Journal of Memory and Language?

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16. Can I download Journal of Memory and Language in Endnote format?

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in Journal of Memory and Language Endnote style according to Elsevier guidelines.

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