Linear regression between ∑PCB and ∑indicator PCB in different study areas. by Matti Viluksela (321291)

Data_Sheet_1_Physiological synchrony in electrodermal activity predicts decreased vigilant attention induced by sleep deprivation.docx by Ivo V. Stuldreher (11897870)

Patients with high baseline gut richness and diversity have significantly greater decreases in diversity over time. by Molly B. El Alam (10231830)

Performance of neural network and linear regression compared to real stock market. by Dania AL-Najjar (11840857)

Subjects:

Analysis of sleep duration and FT3 using segmented linear regression. by Mingzheng Wang (4918222)

Intra-rater and inter-rater agreement of subjective image quality score. by Min Su Park (744914)

Blue line: Normalized time series of new daily confirmed cases in 4 countries with increased noise/signal ratio. by Erick Giovani Sperandio Nascimento (6146123)

Expression of candidate essential genes for sexualization significantly increased before the point of no return. by Nobuyoshi Kumagai (7829759)

The oak tree strains display significant differences in nutrient use, and Oak 2 shows resistance to amphotericin B. by Theresa Lange (22403918)

Multivariate Linear Regression Analysis of Factors Associated with Pain Scores (VAS) in Children Aged 7–12. by Myriam Aïche (22290591)

Linear relationships (Spearman’s r (p-value)) the treatment-induced changes in clinical and neurophysiological data. by Soheila Qanbari (20455173)

Subjects:

Clinical parameters and their significance among dengue severity. by Najeeha Talat Iqbal (9248912)

Subjects:

Intra- and inter-observer agreements determined using ICC test. by Nilüfer Ersan (16475129)

Summary statistics from linear models with biomarkers. by Margaret Sunitha Selvaraj (13994016)

Summary statistics from linear models with metabolites. by Margaret Sunitha Selvaraj (13994016)

Predictor importance for predicting stock market using neural network and linear predictor. by Dania AL-Najjar (11840857)

Subjects:

BMI groups by SES. by Krystal Hunter (6820052)

“…For every increase in BMI, there was a decrease in the probability of PTB (OR = 0.923, 95% CI 0.915–0.931, P < 0.001). …”

BMISES_Data_Part2. by Krystal Hunter (6820052)

“…For every increase in BMI, there was a decrease in the probability of PTB (OR = 0.923, 95% CI 0.915–0.931, P < 0.001). …”

Logistic regression for LSES population. by Krystal Hunter (6820052)

“…For every increase in BMI, there was a decrease in the probability of PTB (OR = 0.923, 95% CI 0.915–0.931, P < 0.001). …”

Logistic regression for HSES population. by Krystal Hunter (6820052)

“…For every increase in BMI, there was a decrease in the probability of PTB (OR = 0.923, 95% CI 0.915–0.931, P < 0.001). …”