Sentences with phrase «as modeling variables»

Not exact matches

Even James Hansen regards climate models only as reliable as their inputs, which are exceedingly complex with respect to climate variables.

They clearly did invalidate the old models over the next few years as credit misallocation accelerated, along with the depth and direction of now - unprecedented imbalances and highly self - reinforcing price changes in commodities, real estate, stock markets, and other variables — what George Soros might have cited as extreme cases of reflexivity.

To attribute the entire decline in stock yields to interest rates as if it is a «fair value» relationship is to introduce a profound «omitted variables» bias into the whole analysis, which is exactly what the Fed Model does.

We account for the projected size and earnings of the expanded workforce, as well as the amount of new housing that each city is expected to produce, and we adjust our model's input variables to develop high - and low - range estimates.

There are far few too many variables to model an outcome Entrepreneurship is a long term commitment and as Investors, we are so lucky to jump the ship after a poor quarter, not the promoter who many times has put...

To offset our counterparty risk in the 2 of 2 multi-signature model, as well as our risk of paying enormous mining fees, there may be variable minimum and maximum limits on any given contract at any given time.

The model linked here details a hypothetical payback for investors, with several variables, such as revenue and net income margins, which can be altered for a number of potential scenarios for a Profit Sharing Unit.

With such a model, we would be able to incorporate financial stability threats into our reaction function, if not with absolute precision, then at least as well as we incorporate other economic variables.

David P. Goldman replies: It is true, as Gregory Barr observes, that most economists» models look at other variables than demographics.

As we identify more variables, and as we invent better means to measure, those models, and the best guess they represent will changAs we identify more variables, and as we invent better means to measure, those models, and the best guess they represent will changas we invent better means to measure, those models, and the best guess they represent will change.

Mathematical models, such as the equations for the growth of a population of insects, are used to make quantitative predictions of particular variables.

Operators are facing four big areas of challenge that Technomic sees as transformative, bound to drive changes in how operators approach business: 1) coping with supply chain challenges, including driver shortages; 2) meeting consumer demand for «food with integrity»; 3) dealing with «regulation nation» where industry - disrupting changes may include a higher minimum wage; and 4) incorporating innovations into operations, including new delivery models, variable pricing, self - ordering systems, and robotics.

Tests for trend were performed by including the breastfeeding categories as continuous variables in the regression models.

We then modeled infant weight as a function of proportions of milk feedings given as breastmilk or by bottle with both terms entered simultaneously into the model as continuous variables.

First, a linear regression model was constructed using the latest postnatal weight measurement in grams as the dependent variable and using the breastfeeding medication group (fluoxetine: yes / no) as the independent variable of interest.

A confounding variable was defined for analysis as one for which there was at least a 5 % difference in the regression coefficient estimates for type of feeding in regression models with and without the potential confounding variable.

Variables were retained in the reduced logistic regression model when their presence was determined to confound the association between human milk feeding and infection or sepsis / meningitis, as defined by a change of > 5 % in the regression coefficient for type of feeding when the variable was removed from the full regression model.

In the final model, no variable was retained as an independently significant risk factor, and no variable modified the estimate of the effect of the medication group in a material way (> 10 %).

women allocated to midwife - led continuity models of care were more likely to be attended at birth by a known midwife (RR 7.04, 95 % CI 4.48 to 11.08; participants = 6917; studies = seven); however, the effect estimates for individual studies are highly variable, as reflected in substantial statistical heterogeneity (Tau ² = 0.31; I ² = 94 %; Analysis 1.15).

The analysis was carried out using a logistic binary regression model, with PPH as the outcome variable and built using manual forward selection (with p < 0.05 as the cut - off).

Pain with breastfeeding was modeled as a four - level categorical variable: no pain, mild pain (Likert level 1 — 2), moderate pain (Likert level 3 — 4), and severe pain (Likert level 5 — 10).

The following covariates were considered in this analysis: household size modeled as a categorical variable (categories), marital status (categories), race and ethnicity (categories), maternal age modeled as a categorical variable (categories), parity (categories), education (categories), employment status (categories), maternal occupation (categories), and postnatal WIC participation.

Hospital, doctor, or clinic visits or hospital admissions as a result of any respiratory infection or illness were combined as composite variables reflecting any respiratory morbidity, and the protective effect of breast feeding persisted in all models (p < 0.01).

Taking distributional characteristics into account leads to situations where two variables can not be exchanged in their status as cause and effect without systematically violating assumptions of the model.

In Bohm's model, the quantum weirdness that had so captivated Bohr, Heisenberg, and the rest — and that had so upset young Bell, when parroted by his teachers — arose because certain variables, such as the electron's initial position, could never be specified precisely: efforts to measure the initial position would inevitably disturb the system.

«By comparing the results of the models, it was possible to determine which environmental variables are the most effective in predicting zebra movement, and then use this knowledge to try and infer as to how the zebra make their decisions,» said Gil Bohrer, assistant professor in the Department of Civil, Environmental, and Geodetic Engineering at The Ohio State University, who collaborated on the project.

The sign and size of the bias would depend on the relative magnitude of the average and variance of the underreporting, as well as the covariance between the underreported, and other variables in the model, and would be typically less than the omitted variable bias were these variables to be left out (10, 11).

Applicants that we were unable to classify were categorized as having missing citizenship information, and we included a dummy variable in the model for those cases.

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).

Many of their pseudoscientific models attempt to predict our creditworthiness, giving each of us so - called e-scores, which are based on numerous variables such as our occupation, what our houses are valued at and our spending habits.

Some of the variables controlling the models are not all that well known,» he adds, including forces such as winds, ocean circulation, and how icebergs calve.

The researchers said their new predictive model is a «definite improvement» over current models of geothermal heat flux that don't incorporate as many variables.

The model simulated yields and greenhouse gas savings under 30 years of variable weather conditions as well.

As Qian honed China's weapons systems, scientists in North America and Europe began applying systems approaches to intractable policy problems, modeling them as a collection of inputs and variables linked by direct or inverse relationships and feedback loopAs Qian honed China's weapons systems, scientists in North America and Europe began applying systems approaches to intractable policy problems, modeling them as a collection of inputs and variables linked by direct or inverse relationships and feedback loopas a collection of inputs and variables linked by direct or inverse relationships and feedback loops.

To date, immunizations in human and animal models have yielded antibodies with only limited ability to neutralize HIV [21], [22], [23], [24], except llama heavy chain only antibodies (HCAbs) isolated as individual variable regions (VHH)[25].

Table 4 reports the results of 4 different logistic regression models with the presence of dementia as the outcome variable, using pooled 2000 and 2012 data.

As described in the main text, ordered logistic regression analyses were carried out for each brain region in which social network distances were modeled as a function of local neural response similarities and dyadic dissimilarities in control variables (gender, ethnicity, nationality, age, and handednessAs described in the main text, ordered logistic regression analyses were carried out for each brain region in which social network distances were modeled as a function of local neural response similarities and dyadic dissimilarities in control variables (gender, ethnicity, nationality, age, and handednessas a function of local neural response similarities and dyadic dissimilarities in control variables (gender, ethnicity, nationality, age, and handedness).

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.

As far as I can tell there is no variable in the model to account for this hemisphere effecAs far as I can tell there is no variable in the model to account for this hemisphere effecas I can tell there is no variable in the model to account for this hemisphere effect.

Models were specified either as ordered logistic regressions with categorical social distance as the dependent variable or as logistic regression with a binary indicator of reciprocated friendship as the dependent variable.

The question of how many variables are involved is not as important as whether the models represent reality.

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

Other multivariate models were carried out in which the individual study year was regarded as a continuous variable.

As the basis for the chapter to follow, we provide summaries of the scaled - down global climate model projections for each of these climate variables below.

For studies that reported incidence in each age category, we fitted log - linear model that contained incidence (dependent variable) and consumption (independent variable) with age as a covariate (median age in each age category), and we estimated the relative risk by using an interaction term between age and consumption.

Fifth, we modeled physician and patient age as continuous rather than categorical variables with quadratic and cubic terms to allow for nonlinear associations.

For consumption, we used the midpoint of the reported number of cigarettes per day — for example, three cigarettes per day if the category was one to five cigarettes per day — which we then adjusted for carboxyhaemoglobin and cotinine because this allows for lower inhalation with increasing cigarette consumption as previously established.14 For studies that reported relative risks adjusted for age (or for additional factors), the model contained the logarithm of the relative risk (dependent variable) and consumption (independent variable) using only the midpoint of the cigarettes per day categories.

We used a logistic regression model with 30 - day mortality as an outcome, and the patient - level adjustment variables listed above as explanatory variables to determine each patient's likelihood of death.

Additionally, the betas from the linear model appeared to be interpreted as a ratio, «Only episodes of excessive coughing and heart burn occurred on average > 2 times more in the cattle than in the control community (β > 2)», where the standard interpretation for a beta from a linear model would be a one unit increase in the outcome for a one unit increase in the explanatory variable, i.e. two more episodes of disease.

In projecting climate variables such as temperature, precipitation, and humidity, there is generally a tradeoff between (a) the ability to produce high - resolution projections needed to inform local decisions and model local responses, and (b) the ability to sample uncertainty.