Sentences with phrase «predictor variables for»

Multiple regression was performed using our six predictor variables for the six different love styles.

Analyzing numerous classes of variables, DecisionSet ® has identified predictor variables for win rates, settlement amounts, awards and attorney - litigant decision - making errors.

Predictor variables for marathon race time in recreational female runners.

Discrete - time survival analysis, with person - year the unit of analysis and a logistic link function, was used to examine associations of temporally primary (based on retrospective age - at - onset reports) mental disorders and subsequent first onset of suicidality.29 Time was modeled as a separate dummy predictor variable for each year of life up to age at interview or age at onset of the outcome, whichever came first.

The latter models included a separate dummy predictor variable for each disorder («type dummies») and dummy predictor variables for number of disorders («number dummies»).

Because of the large number of comparisons (each predictor variable for three outcome measures), results were only considered significant at the p <.01.

Not exact matches

Andrew M. Greeley, «Religious Imagery as a Predictor Variable in the General Social Survey,» paper presented at a plenary session of the Society for the Scientific Study of Religion, Chicago, 1984.

Analysis included logistic regression adjusted for predictor variables and standardized perinatal mortality ratios.

Multivariate analyses were performed with logistic regression for outcome variables with paternal depression and other covariates as predictors.

However, in malnourished populations motor development may be a useful predictor of subsequent human function.5 A study conducted in Denmark6 found a positive relationship between breastfeeding duration and an earlier ability to crawl and perform the «pincer grip» after adjusting for potential confounding variables.

A common goal for a statistical research project is to investigate causality, and in particular to draw a conclusion on the effect of changes in the values of predictors or independent variables on response or dependent variables.

Practices and expectations regarding such questions are so variable, they continue, that one study found «country of origin [to be] a strong predictor of students» tolerance for cheating.»

If models must compete against one another, we suggest comparing the model sets with and without each candidate predictor variable, as we did when calculating the summed Akaike weights for each variable (2).

However, there was not a strong multicollinearity between velocity and our other predictor variables (tolerance values for velocity: amphibians = 0.51, mammals = 0.49, birds = 0.52, values differ due to the use of different predictor variable subsets).

To account for demographic differences that might impact social network structure, our model also included binary predictor variables indicating whether subjects in each dyad were of the same or different nationalities, ethnicities, and genders, as well as a variable indicating the age difference between members of each dyad.

Seven environmental variables, which were previously identified as potential predictors for podoconiosis in Ethiopia (Deribe et al., 2015b), were used to model podoconiosis prevalence.

Second, we run a series of teacher - level regressions where the dependent variables are coverage indices for the emphasized content, and our focal predictors are the five policy attributes, controlling for the descriptive variables listed above.

In their analysis, NORC researchers Nick Rabkin and Eric Hedberg test and ultimately confirm the validity of an assumption made with prior SPPA data, that participation in arts lessons and classes is the most significant predictor of arts participation later in life, even after controlling for other variables.

Let denote outcome h for classroom j in school i. Let denote a vector of predictor variables such as class size, years of teacher experience, and an average of test scores from a previous year for members of the classroom.

In addition, studies show that a student's ability to understand fractions in fifth grade is also a predictor of long - term math achievement in high school, even after controlling for IQ, reading ability, and other variables.

The authors examined how motivational and cognitive variables predict reading comprehension, and whether each predictor variable adds unique explanatory power when statistically controlling for the

The unadjusted models only included prior academic achievement as predictor variables, and are shown for comparison purposes only.

In other words, this particular prediction model can not account for 26 % of the cause of current ELA 8th grade scores, «all other things considered» (i.e., the predictor variables that are so highly correlated with test scores in the first place).

This analysis allowed us to control more precisely for demographic variables by covarying sex, age, and years of experience, while accounting for learning style as a predictor of attrition.

When this variable was entered into the model, learning style was no longer a significant predictor of attrition, though there was a near - significant trend for this variable (p =.10) and for experience (p =.10).

No other independent variable is the top - model predictor for more than one education success measure.

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They are looking at many variable non-linear factors, with limited data input, and worthless for predictors.

These are all cell mean values on a grid with 37 latitudes and 72 longitudes, giving nine predictor fields each with 2664 values for three aspects (climatology, seasonal cycle and monthly variability) for each of three variables (OLR, OSR and N).

In 2003, Michaels and John Christy were among the coauthors of a «Test for harmful collinearity among predictor variables used in modeling global temperature.»

Thus, values and affect were stronger predictors of support for tax policies than the socio - demographic variables, with the exception of political ideology.

After controlling for all the variables, police officer and age remained significant predictors for both groups, suggesting that police officers and younger people use SC more frequently as a coping strategy.

Descriptive Statistics (Means and Standard Deviations) for Predictor and Criterion Variables for West Coast, Midwest 1, and Midwest 2 Sites

An intent - to - treat analysis was conducted using univariate analysis of covariance for continuous variables and multivariate analysis of covariance for continuous variables in which the predictor variable comprised multiple scales.

After creating a full model containing all possible confounders, we performed backward elimination, removing variables whose exclusion from the model resulted in < 10 % change in the effect estimate for the predictor variable.

When data on covariates had been collected at both time points (eg, SES or household adults), we used covariates assessed at 9 months for the 9 - month ITSC predictor variable, and covariates assessed at 2 years for the combined 9 - month + 2 - year ITSC variable.

SLA - level predictor variables will include: accessibility (ARIA +), 33 socioeconomic status (using Socio Economic Status for Areas (SEIFA) indexes, four indexes that summarise different aspects of the socioeconomic conditions of people living in an area based upon sets of social and economic information from the Australian Census35); full - time equivalent GPs; medical workers, nurses, pharmacists, Aboriginal health workers and community services workers per 10 000 population; rates of unemployment and labour force participation.

T1 child BMIz and the same potential co-variates were controlled for at step 1 before entering predictor variables at step 2.

Information was collected in the surveys to date the transitions in time - varying variables (eg, respondent's age at birth of siblings and at parental death or divorce), allowing us to redefine these variables for each year of the respondent's life as time - varying predictors of onset of suicidality.

Preliminary descriptive analyses were conducted for each of the control, predictor, and outcome variables.

To put the effect sizes for the hypothesized associations on wave 6 reckless driving into perspective, we re-ran the final model using logistic regressions (for the connections between the wave 6 indicators and the wave 6 latent variables) to obtain odds ratios (OR) for the indirect effects of wave 1 predictors on the individual wave 6 reckless driving items.

Baseline drinking status (ever vs never tried alcohol) did not predict attrition, but to account for attrition bias related to other variables, estimation was carried out after multiple imputation using the standard missing at random assumption (ie, missing data are assumed missing at random conditional on observed predictors included in the model).27 The imputation model included all the predictors in the alcohol models plus a number of auxiliary variables that were not of direct theoretical interest but were nonetheless predictive of missingness so as to improve the quality of the imputations and make the missing at random assumption more plausible.28

The analyses also included age, race / ethnicity (three binary variables for Black, Hispanic and other ethnicity, coded with Whites as the reference group), gender, household income and parental education, media - viewing habits — hours watching television on a school day and how often the participant viewed movies together with his / her parents — and receptivity to alcohol marketing (based on whether or not the adolescent owned alcohol - branded merchandise at waves 2 — 4).31 Family predictors included perceived inhome availability of alcohol, subject - reported parental alcohol use (assessed at the 16 M survey and assumed to be invariant) and perceptions of authoritative parenting (α = 0.80).32 Other covariates included school performance, extracurricular participation, number of friends who used alcohol, weekly spending money, sensation seeking (4 - wave Cronbach's α range = 0.57 — 0.62) 33 and rebelliousness (0.71 — 0.76).34 All survey items are listed in table S1.

Personality: While individual differences have been accounted for previously in the DRIVE model by including coping style and attributional style variables, personality variables represent a significant omission in this area, particularly when considering subjective well - being outcomes where personality has been cited as potentially the most important predictor (Diener et al., 2003).

It remained a significant predictor after having controlled for many concurrent variables that are correlated with young motherhood: antisocial behavior, low education, smoking, drinking, single parent, poverty, and depression.

It also remained a significant predictor after having controlled for more proximal variables that are often considered mediators of young parenthood: parenting practices and family dysfunction.

For the logit - based analyses and the t tests of differences in means, 1 - tailed tests of significance were conducted (α =.05) because we had an a priori prediction about the direction of the effect for each predictor variabFor the logit - based analyses and the t tests of differences in means, 1 - tailed tests of significance were conducted (α =.05) because we had an a priori prediction about the direction of the effect for each predictor variabfor each predictor variable.

Multivariable regression models were considered, but the modest sample size and patterns of missing data did not allow for simultaneous consideration of multiple predictor variables.

For three other variables, life stress, difficult child temperament, and parent — child dysfunction as predictors of the CBCL externalizing scale, lower levels of pretreatment problems were associated with greater treatment gains.

The hypothesis that nation attachment would account for variance in acculturation over and above the other predictor variables was examined with a hierarchical linear model (HLM), where participants (Level 1) were nested in their country of origin (Level 2).