Sentences with phrase «effects regression analysis»

Maternal heavy alcohol use and toddler behavior problems: a fixed effects regression analysis.

Logistic regressions were used to predict the likelihood of recovery at 18 months, and mixed - effects regression analysis was applied to examine the association of severity and rates of improvement across time in the two treatment groups.

Results Mixed effects regression analyses showed that modular treatment produced significantly steeper trajectories of improvement than usual care and standard treatment on multiple Brief Problem Checklist and Top Problems Assessment measures.

For these mixed effects regression analyses, we focused on the BPC total score and the TPA score, but we also examined the BPC internalizing and externalizing scores, the 2 components of the BPC total score.

Not exact matches

This paper examines the day of the week effect in the crypto currency market using a variety of statistical techniques (average analysis, Student's t - test, ANOVA, the Kruskal - Wallis test, and regression analysis with dummy variables) as well as a trading simulation approach.

• In another Australian study, in multivariate logistic regression analyses «feeling close to the unborn baby» and a «high level of knowledge about the effects of passive smoking on baby» were associated with early quit attempts by fathers Moffatt & Stanton (2005).

A logistic regression analysis was conducted to adjust for the effects of variables identified through the bivariate analysis to be associated with either type of feeding or the presence of infection or sepsis / meningitis.

Kaplan - Meier and Cox proportional hazards survival analyses were used in unadjusted and adjusted analyses of the effect of pacifier use on breastfeeding duration.19 Logistic regression modeling was used to evaluate the effect of pacifier timing on breastfeeding duration.20 Significance levels were not adjusted for multiple comparisons.

The effect of study size, age groups at outcome measurement (comparing those aged 16 — 30 y with those aged ≥ 50 y), year of birth, the method of ascertainment of infant feeding status (whether contemporary or recalled over a period of ≥ 5 y) was examined by using meta - regression and sensitivity analysis.

The authors address difficulties that arise from conditions of field implementation, including the estimation of treatment effects under partial treatment implementation, the prevention and analysis of attrition, analysis of nested designs, new analytic developments for both regression discontinuity designs and short interrupted time series, and propensity score analysis.

Practically every scientist uses statistics — from pharmacologists employing regression to understand the relation between the dose of a drug and its effects in the body, to agronomists using analysis of variance to test which fertilizer makes crops grow fastest.

In multiple regression analysis, titers were also significantly increased after both the DI and S protein vaccines with use of alum (p ≤ 0.01); no dosage effect was noted.

We assessed the association between onlineoffline partner dating and UAI, using random - effects logistic regression analysis..

To identify more precisely the independent effects of the multiple factors affecting teachers» choices, we use regression analysis to estimate the separate effects of salary differences and school characteristics on the probability that a teacher will leave a school district in a given year, holding constant a variety of other factors, including class size and the type of community (urban, suburban, or rural) in which the district is located.

Readers need not get caught up in more - complicated analyses, such as significance testing, effect sizes, and even regression - statistical methods that Raymond and Hanushek criticize us for not using.

To be sure, statewide analyses can provide accurate estimates of the impact of school resources — but only if the analyst includes within the statistical model all the factors that affect student performance and, in the standard linear regression model generally favored by RAND, if these factors have a constant, additive effect on student achievement.

We use administrative data from Michigan in a series of regression - discontinuity analyses to study the effects of these reforms on schools and students.

Regression analyses revealed significant differences with medium to large effect sizes among those with service dogs compared to those on the waitlist, including lower depression, higher quality of life, and higher social functioning.

Since our aim is not so much to produce a definitive analysis as to obtain some idea of the existence and magnitude of the effect, we will examine a variety of possibilities... we may plausibly expect... suggests that the area effect in Figs. 5a and 5b is likely to be underestimated... A potential problem here is that area may not be a reliable measure of cumulus activity... Figs 5c and 5d suggest that a simple linear regression may not be entirely appropriate.»

The final argument of [Shaviv and Veizer, 2003]-- that CO2 has a smaller effect on climate than previously thought — is based on a simple regression analysis of smoothed temperature and CO2 reconstructions.

A fairer comparsion would involve also adjusting the observations to account for the effects of internal variablity (e.g. by regression analysis to remove the effects of ENSO and volcanic forcings which the models do not include).

My understanding is that a uniform prior in S (and hence, equivalently, a 1 / Y ^ 2 prior in Y) would be the correct uninformative reference prior (that which has least effect on the posterior PDF) if way stayed with Forster & Gregory's OLS regression method to estimate Y, if and only if the magnitude of the errors in measurements of the surface temperature were much less than combined errors in the measurements of forcings and net radiative balance, the opposite of what Forster & Gregory's error analysis showed.

Looking for any evidence that humanity is cooking the globe, Jiansong Zhou and Ka - Kit Tung (Deducing Multi-decadal Anthropogenic Global Warming Trends Using Multiple Regression Analysis) began by excluding climate change due to natural factors and more specifically, by adding the effects of AMO (Atlantic Multi-decadal Oscillation) trends that alarmists neglected to consider.

We also carried out analyses to examine the effect of potential influence of regression to the mean arising from the fact that high injury numbers might have been a factor in the decision to implement a 20 mph zone in some areas.

In addition, to assess whether there was an independent study effect on pregnancy rates by time period of recruitment into the study (before and after December 31, 2001), we included a time period variable in the multiple logistic regression analysis of the full study sample and found no effect.

All regression analyses will also take account of any effects of the nurse (clustering), so that accurate effects of the intervention, regardless of child and family nurse delivering it, are estimated.

Subgroup analyses: We will examine whether there is evidence that the intervention effect is modified for subgroups within the trial participants using tests of interaction between intervention and child and family factors as follows: parity (first - born vs other), antenatal risks (2 vs 3 or more risk factors at screening), maternal mental health at baseline (high vs low score) 18, 62, 63 and self - efficacy at baseline (poor vs normal mastery) 35 using the regression models described above with additional terms for interaction between subgroup and trial arm.

To explain the moderating effect, according to the regression equation, respectively, take the campus pressure (U) positive and negative standard deviation to draw a simple effect analysis [13], as shown in Figure 2.

A multivariate regression analysis of the 5 outcomes showed that the joint effect of the 10 outcomes was statistically nonsignificant, X210 = 6.30, P >.70.

Multivariate regression analysis revealed that neither DRD2 nor DRD4 had significant independent effects on conduct disorder or antisocial behavior.

Effect of GDM exposure on mean levels of childhood adiposity outcomes in multivariate linear regression analysis

However, linear regression analysis showed that gender had no significant effect on level of somatic symptoms, when the effects of centre and emotional distress were controlled for.

Logistic regression analyses were conducted to estimate the effect of maternal IPV on asthma diagnosed by age 36 months while adjusting for potential confounders (child's sex, age, race / ethnicity, low birth weight, maternal education, economic hardship, and tobacco exposure).

It has been shown that inferences resulting from this analysis are virtually identical no matter which of these outcome measures is used.30 In addition to the covariates previously noted, the regression analysis was repeated to include annual household income, mother's treatment setting (primary vs psychiatric outpatient care), and treatment status of child during the 3 - month follow - up period in order to investigate the further potential confounding effects of these variables.

A multivariate regression analysis of the 5 outcomes showed that there was a statistically significant overall effect, X25 = 22.56, P <.001.

Further logistic regression analyses indicated that the effect of family type on health outcomes was, in most cases, significant after controlling for the 3 social class indicators and child sex.

The results from logistic regression analyses were presented as OR, with the OR from the fixed - effect logistic regression (sibling comparison) having a cluster - specific interpretation.22 All the analyses were reported with 95 % CI.

Methods: Main - and mediation effects were investigated using hierarchical regression analysis.

The effects of relationship dissatisfaction, life events, emotional distress, and demographic variables on the risk of relationship dissolution were examined using logistic regression analyses.

We implemented unadjusted and adjusted analyses (potential prognostic factors listed in table 2) of the outcomes (all quantitative) by using random effects linear regression models fitted by maximum likelihood estimation to allow for the correlation between the responses of participants from the same maternal and child health centre.29 We present means and standard deviations for each trial arm, along with the mean difference between arms, 95 % confidence intervals, and P values.

To investigate whether birth weight exerted differential effects on brain development at different ages, age and birth weight variables were standardized to the whole sample, and regression analyses with these variables, along with their interaction term (birth weight × age), sex, household income, GAF, and scanner, were repeated.

Multiple regression analysis models with dummy variables assessed the effects of IPPE, MSPSS, TAS - 20, Social Sharing, and Mental Rumination on GDS across the subgroups of participants.

We used ordinal logistic - regression analysis to test the independent effects of each variable, adjusting for demographics, child personality, and parenting style.

Multiple regression analyses determined that while both traumatic events and organizational stressors affected psychological distress, organizational stressors had the strongest effect, including the exacerbation of Posttraumatic Stress Disorder symptoms.

To examine the effect of received support and perceived support on psychological well - being, multiple regression analysis was conducted.

Independent sample t - test was used to compare the level of self - esteem, family function score and social support score between the two groups with and without grandparenting experience; Pearson correlation was calculated to explore how levels of self - esteem and family functions as well as perceived social support were related; Hierarchical regression analysis was applied to examine the moderating effect of social support on the relationship between family function and self - esteem.

Analyses were implemented at the level of the individual using random effects (multilevel) linear regression models24 fitted using maximum - likelihood estimation to allow for the correlation (or clustering) between the responses of subjects from the same MCH unit.

To examine whether the relationship between pubertal status and neural response to social evaluation differed for healthy youth and controls, similar whole brain regression analyses were conducted to identify areas showing group × pubertal status interaction effects.

Hierarchical regression analyses were conducted to examine the effects of friendship quality on the adolescents» well - being as a function of country and hearing status.

Hierarchical regression analyses were conducted to examine the effect of pc use with a friend, country, hearing status, school setting and age on the online, mixed and offline friendship quality.