ESEM 3 F delta df=36; delta WLSMVchi^2=152.04, p<.001
BCFA 3 s F delta df=186; delta WLSMVchi^2=80.31, p<.001
BESEM 3 s F delta df=186; delta WLSMVchi^2=218.82, p<.001
ESEM 3 F delta df=18; delta WLSMVchi^2=84.32, p<.001
BESEM 3 s F delta df=36; delta WLSMVchi^2=152.30, p<.001
BESEM 3 s F delta df=18; delta WLSMVchi^2=74.11, p<.001

Prognostic value of postoperative serum carcinoembryonic antigen levels in colorectal cancer patients who smoke

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Socioeconomic characteristics, family structure and trajectories of children's psychosocial problems in a period of social transition

Neural correlates of sense of agency in motor control: A neuroimaging meta-analysis

Internet, unmet aspirations and the U-shape of life

2sls recursive bivariate ordered probit model

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'I wanted to go, but they said wait': Mothers' bargaining power and strategies in care-seeking for ill newborns in Ethiopia

A qualitative study on the reasons for solitary eating habits of older adults living with family

Depression and suicidal behavior in LGB and heterosexual populations in Serbia and their differences: Cross-sectional study

suicidal attempts 27 Odds Ratio OR=27.31

Unsupervised acquisition of idiomatic units of symbolic natural language: An n-gram frequency-based approach for the chunking of news articles and tweets

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studies evaluating supervised learning method
result may favor unsupervised text chunking model

pone.0234214.e010">removedGRAPHIC F b=(1 + b 2) - P - R (b 2 - P) + R</disp formula><disp formula id="pone.0234214.e011">removedGRAPHIC F b=1=2 - P - R P + R</disp formula><disp formula id="pone.0234214.e012

Participatory modelling for poverty alleviation using fuzzy cognitive maps and OWA learning aggregation

n -1 ∑ i=1 n (n -1) w i</disp formula>As suggested by Yager (14
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pone.0233984.e026">removedGRAPHIC X i (t + 1)=f (∑ j=1