The phrase "in which correlation" is grammatically correct and can be used in written English.
It is typically used to introduce a clause or phrase that explains or expands upon a correlation mentioned in the preceding sentence. Example: "The researchers found a strong correlation between income level and access to healthcare, in which correlation those with higher incomes had better access to medical services."
The correlation matrix, in which correlation coefficients are arranged in a matrix consisting of individual elements/isotopes to be correlated to show the correlation coefficient at their intersection cell (Figure 2), shows an overall data structure.
Study design: Case study in which correlation was made between immunoglobulin response to influenza vaccination to the disease and its unique clinical course caused by influenza virus.
Thus, P-PLS decomposes the whole input and output data space into only 4 subspaces, in which correlation subspace, unpredictable output principal subspace and unpredictable output residual subspace are output-relevant and input-residual subspace is input-relevant.
In this paper, a new recovery algorithm is presented, in which correlation analysis of WLI envelop curves and a multi reference position based phase solution method are employed for robust and high precision surface recovery.
In which, correlation of H-9 with H-12 indicated both protons located at the same side.
Of particular interest are cases in which one can tune the competition between different types of correlation, or in which correlation can be tunably enhanced or suppressed by other effects (such as confinement or interference), potentially causing a quantum phase transition a sudden, qualitative change in the correlations in the system.
Three sets of analyses were used: correlational analyses, in which correlations between independent variables and brain volumes were calculated without correction for intracranial volume (ICV); covariational analyses, in which ICV was used as a covariate in regression equations; and ratio analyses, in which the dependent variable was the ratio of brain volume to ICV.
The two bi-factor models included: one with orthogonal factors, i.e., in which the model does not allow factors to correlate with one another; and an oblique one in which correlations between factors are allowed.
Poor selection can result in confounding, in which correlations that are unrelated to the exposure exist between case and control subjects.
Unlike clinic-based studies in which correlations are almost nonexistent, the population-based studies demonstrate a modest correlation among lower urinary tract symptoms, peak urinary flow rates, and prostatic volume.
Although this assumption is often valid, there are cases in which correlations between the generalised forces can significantly affect the response variance, and in the present work the existing theory is extended to include correlations of this type.
