Sentences with phrase «with imputation»

The problem with imputation is that it tames the data, reducing outliers and reinforcing the means.

Not exact matches

Bill Shorten's plan to ditch the cash refund on dividend imputation credits is at odds with his aim of robbing Peter to pay Paul and if the...

The imputation of Christ's righteousness as the basis for reconciliation with God.

The word imputation (not used in the body of the document) refers to God's crediting of righteousness to us because of what Christ has done for us: which means, God's accounting of Christ's righteousness to all those who are united with him through faith.

The strength of the association between early breastfeeding experience and postpartum depression was similar in magnitude when comparing the complete case with the multiple imputation analyses.

Title: Combining efficacy and completion rates with no data imputation: a composite approach with greater sensitivity for the statistical evaluation of active comparisons in antipsychotic Trials Author: J. Rabinowitz et al..

A new GWAS and meta - analysis with 1000Genomes imputation identifies novel risk variants for colorectal cancer.

The discussion will continue with a demonstration of how HLM 7 can use multiple imputation to impute data when missingness is an issue.

One way to deal with this issue is the imputation of missing values.

For all variables with missing values, the project uses STATA implementation of the Monte Carlo Markov Chain (MCMC) multiple imputation algorithm that generates five plausible values for each variable based on non-missing values for every other variable.

In this project, multiple imputation is used to deal with missing data.

The introduction of dividend imputation in 1987 removed the double taxation of dividends, with tax - resident Australian companies receiving a «franking credit» for tax paid at prevailing corporate tax rates.

If the income is from «franked» dividends - that is, dividends paid by an Australian company out of profits on which it has already paid tax - it will come with a credit for the tax already paid, called an «imputation credit».

Given that we do not disagree with the results of the research on the faux «pause» — how could we, having contributed to it — and given that the disagreement between Betts and us seems to boil down primarily to semantics and the imputation of scientists» motivations, does it matter whether or not there is «seepage» into the scientific community?

Why should those who scientifically understand that global warming is definitely happening put up with Norton's imputation that they are implicated in some «dogmatically insisting».

Discussing these things on a limited basis with one very close friend, relative or professional is probably healthy but disgorging and rehearsing every event, feeling and fear to multiple people multiple times each week only serves to magnify the complaints and exacerbate the fear and results in exaggerated suspicions and the imputation of deception and dishonesty to your spouse, resulting in an inability to ever be satisfied with the answers demonstrated by even the most credible evidence.

Keep in mind that the burden rests with the party arguing for imputation of income to provide some evidentiary basis to show that the other party is intentionally under or unemployed, including for example the other side's education, work experience, skills, health and a failure to produce documentation of sincere job - seeking efforts.

If the concept of imputation were applied with unqualified rigor, the result would be radical curtailment of the opportunity of lawyers to move from one practice setting to another and of the opportunity of clients to change counsel.

The consistency of primary analyses with those based on multiple imputation suggests that results are robust to data that are missing at random, although of course we were unable to evaluate bias associated with unobserved variables.

Finally, analyses were conducted and compared using both the imputed data set, and a subset of data containing only participants with complete data, and indicated no bias resulting from imputation.

Missing data: The frequency and patterns of missing data will be examined and sensitivity analyses will be performed to compare the results of analyses restricted to families with complete data and analyses where those with missing data are considered using multiple imputation.64, 65

To account for missing poverty data, we used UVIS (univariate imputation sampling) in Stata version 10,15 which imputes a variable using logit regression with sociodemographic variables having significant statistical association with nonmissing poverty data (child age, maternal obesity, maternal education, and race / ethnicity).

We used multiple imputation with the method of chained equations to account for missing maternal data for children with a mother in the household.24 In addition to the mother's BMI status (missing for 1085 [22 %] of the children), imputation was conducted for 4 maternal covariates with few (< 1 %) missing cases (education [n = 13], warmth [n = 47], control [n = 49], and irritability [n = 48]-RRB-.

There were no differences in either anthropometric measures at age 6 years or socioeconomic variables between children with BMI data at age 4 years and those without it, and analyses including all children produced findings consistent with those obtained using multiple imputation.

In general, multiple imputation imputes missing scale values with regression - based maximal likelihood procedures but also incorporates random error into the estimates.26 To improve estimates, key demographic factors and the important covariates were used in the imputation strategy, and the procedures described by Allison27 for intervention studies were used.

The multiple imputation procedure, which is one of the most recommended procedures to deal with missing values with the pattern of Missing at Random (see Schlomer et al., 2010, for a simulation study), was used to handle missing values.

Fit indices used to evaluate the model included a χ2 goodness - of - fit test (nonsignificant values indicate good fits), the comparative fit index (scores of > 0.95 indicate better fits), the root mean square error of approximation (values of < 0.05 indicate good fits), and the standardized root mean square residual (values of < 0.08 indicate good fits).43, 44 Missing values were imputed through multiple imputation by using functions in the missing data library in S - Plus (Insightful Corp, Seattle, WA).45, 46 The combined data for the cross - lagged / survival model converged more quickly with 15 imputed data sets than did the model that used a likelihood - based approach to missing data.

However, this concern regarding bias has been diminished through the inclusion of adolescents with incomplete data, through imputation.

Multiple imputation was carried out using the chained equations approach to deal with missing data.

Because of substantial missing data on 2 direct parenting measures (29 %), multiple imputation via chained equations was used to handle missing covariate data.30 This approach uses regression models to predict missing data from available variables with 20 imputation iterations selected.

Multiple logistic regression models, with the use of multiple imputation to account for missing data, assessed the associations between probable DCD and mental health difficulties.

Missing values (missing completely at random)(10.5 %) were imputed with single imputation method.

While some of the records with unknown Indigenous status will be for people of Aboriginal and / or Torres Strait Islander origin and others for non-Indigenous people, no imputation was made for Indigenous status on the Census file.

Imputation of Indigenous status for Census records with unknown Indigenous status (as a result of either non-response to the Aboriginal and Torres Strait Islander origin question in the Census, or unknown Indigenous status on Census records imputed by the Australian Bureau of Statistics (ABS) when a form could not be obtained from occupied dwellings identified in the field);

Missing data will in the first instance be managed with a «last observation carried forward» approach with additional sensitivity analyses undertaken using multiple imputation methods.

Missing data for specific time points and from loss to follow - up will be dealt with through multivariate multiple imputation or full information maximum likelihood methods as appropriate.

Similarly, the complete - case analysis implies that drinking alcohol is negatively associated with internalizing problems; after imputation, that relation is insignificant and there is evidence of a significant positive association between smoking and internalizing problems.

Dealing with missing data in a multi-question depression scale: a comparison of imputation methods [electronic article]

Longitudinal modeling with randomly and systematically missing data: A simulation of ad hoc, maximum likelihood, and multiple imputation techniques

All computations were carried out with Mice (Van Buuren and Groothuis - Oudshoorn 2011) in R (R Core Team 2014), with 150 iterations for the algorithm to converge and 25 multiply imputed datasets, using available and custom imputation routines.