2020
DOI: 10.1016/j.physbeh.2020.112904
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T-patterns integration strategy in a longitudinal study: a multiple case analysis

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Cited by 16 publications
(12 citation statements)
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“…T-patterns, or temporal patterns, are essentially a combination of events that occur in the same order, separated by temporal distances that remain invariant over time. The basic premise of T-pattern detection is that the interactive flow or chain of behaviors consists of structures of variable stability that can be visualized through the detection of underlying T-patterns ( Suárez et al, 2018 ; Portell et al, 2019 ; Santoyo et al, 2020 ). As indicated by Magnusson(2020 , p. 2): “As a Mixed Methods approach, T-pattern analysis […] passes repeatedly between qualitative and quantitative analyses, from data collection logging the occurrences of qualities (categories) and their real-time (quantitative) locations resulting in time-stamped data, here T-data, to the detection of T-patterns (qualities) […], typically followed by both qualitative and quantitative analyses of the detected patterns.” T-pattern analysis involves the use of an algorithm that calculates temporal distances between codes of behaviors, analyzing the extent to which the critical interval remains invariant relative to the null hypothesis.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…T-patterns, or temporal patterns, are essentially a combination of events that occur in the same order, separated by temporal distances that remain invariant over time. The basic premise of T-pattern detection is that the interactive flow or chain of behaviors consists of structures of variable stability that can be visualized through the detection of underlying T-patterns ( Suárez et al, 2018 ; Portell et al, 2019 ; Santoyo et al, 2020 ). As indicated by Magnusson(2020 , p. 2): “As a Mixed Methods approach, T-pattern analysis […] passes repeatedly between qualitative and quantitative analyses, from data collection logging the occurrences of qualities (categories) and their real-time (quantitative) locations resulting in time-stamped data, here T-data, to the detection of T-patterns (qualities) […], typically followed by both qualitative and quantitative analyses of the detected patterns.” T-pattern analysis involves the use of an algorithm that calculates temporal distances between codes of behaviors, analyzing the extent to which the critical interval remains invariant relative to the null hypothesis.…”
Section: Methodsmentioning
confidence: 99%
“…T-patterns, or temporal patterns, are essentially a combination of events that occur in the same order, separated by temporal distances that remain invariant over time. The basic premise of T-pattern detection is that the interactive flow or chain of behaviors consists of structures of variable stability that can be visualized through the detection of underlying T-patterns (Suárez et al, 2018;Portell et al, 2019;Santoyo et al, 2020). As indicated by Magnusson (2020, p. 2): "As a Mixed Methods approach, T-pattern analysis [.…”
Section: T-pattern Detectionmentioning
confidence: 99%
“…Following [26] 'if A is an earlier and B a later component of the same recurring T-pattern, then, after an occurrence of A at t, there is an interval [t + d1, t + d2] (d2 ≥ d1 ≥ d0) that tends to contain at least one occurrence of B more often than would be expected by chance'. The search parameters when applying TPA were: (i) Level of significance for the critical interval (p < 0.005) [29,30], (ii) The most complex T-Patterns were based on 5 occurrences; (iii) Selection of free heuristic critical interval setting [31], (iv) TPA detection were validated by simulation, through data randomization [29,32].…”
Section: T-pattern Analysismentioning
confidence: 99%
“…The authors will also try to design studies considering the use of new instruments and strategies for data analysis [48,49].…”
Section: Conflicts Of Interestmentioning
confidence: 99%