multivariate regression models

USAGE SUMMARY

The phrase "multivariate regression models" is correct and usable in written English.
It can be used in statistical or research contexts when discussing models that analyze multiple variables simultaneously to understand their relationships. Example: "In our study, we employed multivariate regression models to assess the impact of various factors on consumer behavior."

✓ Grammatically correct

Science

Academia

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

Factors associated with depressive symptoms, including socioeconomic status, QOL indices, and associated chronic diseases, were investigated using multivariate regression models.

Harvard University

using multivariate regression models in the function of geomorphological, climatic and stand factors.

Ecological Modelling

Multivariate regression models examined reported lifetime NSSI.

Health & Justice

Multivariate regression models assessed predictors of erythropoietin prescription.

Duke University

Adjusted multivariate regression models were used to examine group differences.

Duke University

We assessed associations among beverage prices, energy intake, and weight using multivariate regression models.

Duke University

Multivariate regression models were constructed to adjust for baseline differences between SSRI and control groups.

Duke University

Multivariate regression models were used to estimate the incremental expenditures attributable to back pain.

Duke University

Note: "Ref" indicates the reference category for the discrete variable in the multivariate regression models.

IZA Journal of Labor Policy

Consequently we set up various multivariate regression models in order to control for such effects.

Large-scale Assessments in Education

Hosmer Lemeshow goodness-of-fit tests were performed on multivariate regression models.

Annals of Intensive Care

Expert writing Tips

Best practice

When describing your statistical methods, explicitly state the type of "multivariate regression models" used (e.g., linear, logistic) to provide clarity and ensure reproducibility.

Common error

Avoid attributing causation solely based on the results of "multivariate regression models". These models demonstrate associations, but further analysis and theoretical justification are needed to establish causality.

Linguistic Context

The phrase "multivariate regression models" functions as a noun phrase that identifies a specific class of statistical models. These models are used to analyze the relationship between multiple independent variables and one or more dependent variables. As Ludwig AI confirms, this is a common and acceptable phrase in academic and scientific writing.

Expression frequency: Very common

Frequent in

Science

55%

Academia

45%

News & Media

0%

Less common in

Formal & Business

0%

Encyclopedias

0%

Wiki

0%

Ludwig's WRAP-UP

In summary, "multivariate regression models" is a grammatically correct and frequently used term, as validated by Ludwig AI, referring to statistical models that analyze the relationship between multiple independent variables and one or more dependent variables. Predominantly found in scientific and academic contexts, these models are crucial for understanding complex relationships in various research fields. When writing about these models, it's important to specify the type and avoid misinterpreting correlation as causation. Alternatives include "multiple regression models" and "multivariable regression models", though they may subtly shift the focus.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

multiple regression models

Replaces "multivariate" with "multiple", focusing on the presence of several independent variables.

multivariable regression models

Uses "multivariable" instead of "multivariate", which is a common synonym in many statistical contexts.

regression models for multiple variables

Rephrases the concept to emphasize the application of regression to several variables.

regression analysis with multiple predictors

Shifts focus to the analytical process and highlights the use of multiple predictor variables.

statistical models for multivariate data

Broadens the scope to include any statistical model applicable to multivariate data, not just regression.

models using multiple independent variables

Emphasizes the structure of the model regarding its input variables.

multivariate statistical analysis

Focuses on the broader statistical technique that includes regression as a specific application.

complex regression models

Highlights the complexity introduced by multiple variables in the regression model.

regression models with interaction terms

Specifies a particular type of multivariate regression that includes interaction effects.

simultaneous equation models

Implies a system of equations being modeled simultaneously, which is a type of multivariate regression.

FAQs

How are "multivariate regression models" used in research?

"Multivariate regression models" are employed to analyze the relationship between multiple independent variables and one or more dependent variables, allowing researchers to understand the combined effect of several factors.

What's the difference between "multivariate regression models" and simple linear regression?

Simple linear regression examines the relationship between a single independent variable and a dependent variable, while "multivariate regression models" assess the relationships between multiple independent variables and one or more dependent variables.

When should I use "multivariate regression models" instead of running multiple individual regressions?

Use "multivariate regression models" when you suspect that independent variables are correlated or when you want to control for confounding variables, providing a more accurate understanding of each variable's unique contribution. If you don't need to control confounding variables, you can use "individual regressions".

What are some potential alternatives to "multivariate regression models"?

Depending on the research question and data characteristics, alternatives to "multivariate regression models" include "structural equation modeling", "multilevel modeling", or "machine learning algorithms".