scholarly journals Estimating functional linear mixed-effects regression models

2017 ◽  
Vol 106 ◽  
pp. 153-164 ◽  
Author(s):  
Baisen Liu ◽  
Liangliang Wang ◽  
Jiguo Cao
Keyword(s):  
Regression Models ◽  
Mixed Effects ◽  
Linear Mixed Effects

scholarly journals Statistical analysis of comparative tumor growth repeated measures experiments in the ovarian cancer patient derived xenograft (PDX) setting

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ann L. Oberg ◽  
Ethan P. Heinzen ◽  
Xiaonan Hou ◽  
Mariam M. Al Hilli ◽  
Rachel M. Hurley ◽  
...  
Keyword(s):  
Tumor Growth ◽  
Repeated Measures ◽  
Regression Models ◽  
Statistical Power ◽  
Mixed Effects ◽  
Information Criteria ◽  
Tumor Doubling Time ◽  
Linear Mixed Effects ◽  
Patient Derived Xenograft ◽  
Pdx Models

AbstractRepeated measures studies are frequently performed in patient-derived xenograft (PDX) models to evaluate drug activity or compare effectiveness of cancer treatment regimens. Linear mixed effects regression models were used to perform statistical modeling of tumor growth data. Biologically plausible structures for the covariation between repeated tumor burden measurements are explained. Graphical, tabular, and information criteria tools useful for choosing the mean model functional form and covariation structure are demonstrated in a Case Study of five PDX models comparing cancer treatments. Power calculations were performed via simulation. Linear mixed effects regression models applied to the natural log scale were shown to describe the observed data well. A straight growth function fit well for two PDX models. Three PDX models required quadratic or cubic polynomial (time squared or cubed) terms to describe delayed tumor regression or initial tumor growth followed by regression. Spatial(power), spatial(power) + RE, and RE covariance structures were found to be reasonable. Statistical power is shown as a function of sample size for different levels of variation. Linear mixed effects regression models provide a unified and flexible framework for analysis of PDX repeated measures data, use all available data, and allow estimation of tumor doubling time.

scholarly journals Effects of Spacing on Sentence Reading in Chinese

2021 ◽  
Vol 12 ◽  
Author(s):  
Gaisha Oralova ◽  
Victor Kuperman
Keyword(s):  
Regression Models ◽  
Native Speaker ◽  
Mixed Effects ◽  
The Other ◽  
Word Boundary ◽  
Linear Mixed Effects ◽  
Sentence Reading ◽  
Word Boundaries ◽  
Theories Of Reading ◽  
Chinese Writing

Given that Chinese writing conventions lack inter-word spacing, understanding whether and how readers of Chinese segment regular unspaced Chinese writing into words is an important question for theories of reading. This study examined the processing outcomes of introducing spaces to written Chinese sentences in varying positions based on native speaker consensus. The measure of consensus for every character transition in our stimuli sentences was the percent of raters who placed a word boundary in that position. The eye movements of native readers of Chinese were recorded while they silently read original unspaced sentences and their experimentally manipulated counterparts for comprehension. We introduced two types of spaced sentences: one with spaces inserted at every probable word boundary (heavily spaced), and another with spaces placed only at highly probable word boundaries (lightly spaced). Linear mixed-effects regression models showed that heavily spaced sentences took identical time to read as unspaced ones despite the shortened fixation times on individual words (Experiment 1). On the other hand, reading times for lightly spaced sentences and words were shorter than those for unspaced ones (Experiment 2). Thus, spaces proved to be advantageous but only when introduced at highly probable word boundaries. We discuss methodological and theoretical implications of these findings.

scholarly journals Heightened Stress Reactivity in Response to an Attachment Related Stressor in Patients With Medically Treated Primary Hypertension

2021 ◽  
Vol 12 ◽  
Author(s):  
Elisabeth M. Balint ◽  
Marc N. Jarczok ◽  
Dominik Langgartner ◽  
Stefan O. Reber ◽  
Simon Endes ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
Arterial Stiffness ◽  
Regression Models ◽  
Stress Reactivity ◽  
Mixed Effects ◽  
Primary Hypertension ◽  
Healthy Controls ◽  
Hypertensive Patients ◽  
Linear Mixed Effects

Background: A heightened stress reactivity to mental stress tasks has been shown in hypertensive patients and might contribute to a higher disease risk. We investigated this hyperreactivity with regard to an attachment related stressor that focuses on emotions instead of performance and we examined whether this effect can also be found in patients on antihypertensive drugs.Materials and Methods: Fifty patients with primary hypertension, treated with at least one antihypertensive drug, were compared with 25 healthy individuals. After 10 min of rest, they participated in an attachment-related interview (Adult Attachment Projective picture system, AAP) and were exposed to an attachment-related stressor (Separation Recall, SR), a short-time stressor which activates attachment-related emotions and thoughts by talking 5 min about a personal experience of loneliness. Blood samples to measure adrenocorticotrope hormone (ACTH), cortisol, norepinephrine, epinephrine, and dopamine were taken. Blood pressure, heart rate and arterial stiffness were measured at rest, after AAP, after SR and 10 min after recovery. Standard deviation of normal-to-normal intervals (SDNN) and root mean square of successive differences (RMSSD) were calculated. Parameters were compared using Mann Whitney U-test and linear mixed-effects regression models controlling for age and body mass index (BMI) after logarithmic transformation if appropriate.Results: Healthy test persons were younger and had lower BMI than patients. Comparing the two groups there were no significant differences in blood pressure and heart rate at rest. Both stressors provoked a significant response in almost all parameters. Results of the post-estimation of contrasts from linear mixed-effects regression models showed a steeper rise in systolic BP and arterial stiffness as well as a more pronounced decline in SDNN in hypertensive patients than in healthy controls. Levels of cortisol rose earlier and higher in hypertensive patients than in healthy controls.Conclusion: Vascular, autonomic, and hypothalamic pituitary adrenal axis response is heightened in medicated subjects with hypertension in response to attachment-focused stressors compared to healthy subjects. We conclude that the remaining hyper-reactivity even with sufficient antihypertensive medication still poses a substantial risk for affected patients. New ways to diminish this risk should be developed.

A Multivariate Approach to Lexical Diversity in Constrained Language

2020 ◽  
Vol 21 (2) ◽  
pp. 169-194
Author(s):  
Marta Kajzer-Wietrzny ◽  
Ilmari Ivaska
Keyword(s):  
Second Language Acquisition ◽  
Regression Models ◽  
Translation Studies ◽  
Methodological Framework ◽  
Multivariate Approach ◽  
Mediated Communication ◽  
Vocabulary Size ◽  
Lexical Diversity ◽  
Linear Mixed Effects ◽  
Word Repetition

Empirical Translation Studies have recently extended the scope of research to other forms of constrained and mediated communication, including bilingual communication, editing, and intralingual translation. Despite the diversity of factors accounted for so far, this new strand of research is yet to take the leap into intermodal comparisons. In this paper we look at Lexical Diversity (LD), which under different guises, has been studied both within Translation Studies (TS) and Second Language Acquisition (SLA). LD refers to the rate of word repetition, and vocabulary size and depth, and previous research indicates that translated and non-native language tends to be less lexically diverse. There is, however, no study that would investigate both varieties within a unified methodological framework. The study reported here looks at LD in spoken and written modes of constrained and non-constrained language. In a two-step analysis involving Exploratory Factor Analysis and linear mixed-effects regression models we find interpretations to be least lexically diverse and written non-constrained texts to be most diverse. Speeches delivered impromptu are less diverse than those read out loud and the non-constrained texts are more sensitive to such delivery-related differences than the constrained ones.

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