The average spearman rank correlation coefficient

Lyerly, Samuel B.

doi:10.1007/bf02288917

Cited by 92 publications

(32 citation statements)

References 4 publications

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“…1 shows that the number of words recalled immediately increased during the baseline period for both practice groups and reached highest levels during the first recovery session. The Lyerly average rank-order test (Lyerly, 1952;Lubin, 1961) applied to t h e baseline scores showed that for both groups, this effect was significant. "^ control for practice, an interpolated residual score (Williams LQ Lubin, in press) was calculated by subtracting the linear interpolated residual score based on last baseline and first recovery sessions from the observed number of correct answers on each sleep-loss session:…”

Section: Methodsmentioning

confidence: 96%

Some Effects of Sleep Loss on Memory

Williams

Gieseking

Lubin³

1966

Percept Mot Skills

104

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Immediate recall of word lists showed significant impairment after one night of sleep loss. Since S was required to write down each word immediately after its presentation, the deficit was not due to failure of sensory registration. With 24-hr, delayed testing, a picmre-recognition test did not show significant deficit after one night of sleep loss. Performance on this test was impaired, however, after a night of recovery sleep. These results imply that moderate sleep loss causes deficit in formation of the memory trace rather than in storage or retrieval functions and that this effect is probably independent of the physiological lapses (brief periods of sleep) which affect vigilance and sensory registration.As Weiner ( 1966) pointed out, most theorists see memory as consisting of a sequence of processes such as sensory registration, memory-trace formation, trace storage and retrieval. An important problem for the investigator of memory deficit is to specify which of these functions is impaired by a given experimental treatment. For example, memory deficit found with sleep deprivation (Patrick & Gilbert, 1896; Weiskotten & Ferguson, 1930;Edwards, 1941) could result from impairment of any or all of the functions mentioned by Weiner.Gieseking, Williams, and Lubin (1957) found that sleep deprivation caused progressive deficit in retention of general information items. Immediate recall scores deteriorated significantly after one night of sleep loss, with increasing decrement as sleep loss increased. Relative to immediate recall, delayed recall (24 hr. after initial presentation) showed no significant sleep-loss decrement up to 50 hr. of wakefulness. Williams, Lubin, and Goodnow (1959) attributed the deterioration of immediate memory to the occurrence of lapses (periods of sleep lasting 3 or 4 sec.) which were known to increase in frequency and duration as sleep loss increased. If a lapse occurred during the presentation of an information item, S might fail to register it for later recall. An adequate test of this explanation requires that sensory registration be brought under control. The experiments reported here attempted to confirm the deleterious effects of acute sleep loss on memory previously reported and to indicate which memory functions were most sensitive t o sleep loss. There are cwo experiments. The first tests whether sleep loss leads to impairment of immediate recall under con- 'We wish to thank Mrs. Elizabeth Engle, Mrs. Ometta Kearney, and Miss Betty Shanks for their assistance in test administration and statistical analysis.

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Section: Methodsmentioning

confidence: 96%

Some Effects of Sleep Loss on Memory

Williams

Gieseking

Lubin³

1966

Percept Mot Skills

104

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“…(We term these pairwise correlations between educators and the Blackbox data: educator accord.) This use of the average was originally recommended by Lyerly [13], then explained and generalised by Taylor and Fong [21,20] to add a significance test. In our example, Taylor'sρt,c is the average of the pairwise correlations between the Blackbox data and each educator, corrected for continuity.…”

Section: Educator and Student Agreementmentioning

confidence: 99%

Investigating novice programming mistakes

Brown

Altadmri

2014

Proceedings of the Tenth Annual Conference on International Computing Education Research

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Educators often form opinions on which programming mistakes novices make most often -for example, in Java: "they always confuse equality with assignment", or "they always call methods with the wrong types". These opinions are generally based solely on personal experience. We report a study to determine if programming educators form a consensus about which Java programming mistakes are the most common. We used the Blackbox data set to check whether the educators' opinions matched data from over 100,000 students -and checked whether this agreement was mediated by educators' experience. We found that educators formed only a weak consensus about which mistakes are most frequent, that their rankings bore only a moderate correspondence to the students in the Blackbox data, and that educators' experience had no effect on this level of agreement. These results raise questions about claims educators make regarding which errors students are most likely to commit.

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“…It is an unstandardized ES measure of a monotonic trend in data. To convert L into a standardized ES, one divides Page's L (i.e., the average ρ) by its standard deviation (Lyerly, 1952;Page, 1963, p. 227) to yield a standardized normal z, as in (5) populations (Cohen, 1988), whereas the standardized L, or the normalized z in (5), does not, because the latter is based on ranks of the data.…”

Section: Six Es Measures Derived From Page's Lmentioning

confidence: 99%

“…Since the standardized L, or z from (5), follows a standard normal distribution (e.g., Fahoome, 2002;Lyerly, 1952), a nondirectional 95% CI for the standardized L can be constructed using (6) …”

Section: For the Standardized Es Derived From Page's Lmentioning

confidence: 99%

Algorithms for Assessing Intervention Effects in Single-Case Studies

Peng¹,

Chen²

2015

J. Mod. App. Stat. Meth.

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Free web-based resources or popular software to assess six data features recommended by the What Works Clearinghouse: Procedures and Standards Handbook (IES, 2013 February) to determine intervention effects in a single-case study (Lambert, Cartledge, Heward, & Lo, 2006) are demonstrated. Lambert et al. (2006) employed a reversal (or ABAB) design and visual inspection to investigate the effectiveness of the report-card treatment in reducing disruptive behaviors in students. In our demonstration, we assessed each of the six data features separately; then integrated six assessments into one comprehensive analysis of the intervention effect. A simple approach to the determination of intervention effects illustrates how researchers and practitioners can be empowered to interpret data comprehensively and formulate evidence-based conclusions logically from well-designed and well-executed single-case studies.

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The average spearman rank correlation coefficient

Cited by 92 publications

References 4 publications

Some Effects of Sleep Loss on Memory

Some Effects of Sleep Loss on Memory

Investigating novice programming mistakes

Algorithms for Assessing Intervention Effects in Single-Case Studies

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