Chapter 31 - 33

approach uses data and prior beliefs (the priors) to predict the likelihood of a particular outcome (the posterior)

Bayesian

set of conditions that provide support for the existence of a causal relationship between an exposure and an outcome

Bradford Hill criteria

assesses the homogeneity of stratum specific measures of association

Breslow Day test

type of regression model that estimates a hazard ratio

Cox proportional hazards

time graph that displays cumulative survival rates in a study population

Kaplan Meier plot

weighting method can adjust odds ratio or other measures of association for an exposure variable and an outcome variable after using a third variable to stratify the data

Mantel Haenszel

methods are stochastic processes that use algorithms to take samples from stimulated probability distributions

Markov chain Mote Carlo (MCMC)

tests for spatial autocorrelation, which is a measurement of how similar one location is to nearby places

Moran's I coefficient

compartmental mathematical model of infection transmission that describes how the susceptible (S) individuals in a population may become infected (I) and then eventually recover (R) with immunity

SIR model

developed before the start of data analysis

a priori codes

makes inferences based on limited observation and minor premises, so the conclusions are assumed to be best guesses that are merely probable

abduction

uses computers to stimulate the actions and interaction of various individuals (agents) in a population

agent based modeling/individual based modeling

relationship between two variables

association

pattern in which a variable measured over times has values influenced by its own past values as per a Durbin Watson test or another test statistic or, in spatial analysis, a measurement of how similar one location is to nearby places

autocorrelation

identifies one core category or core phenomenon and several related categories that express the major and minor themes of the analysis

axial coding

deletes predictor variables from the model until deleting a variable significantly reduces the overall fit of the model

backward stepwise method

describes the adverse impact of a particular health condition on a population

burden of disease

identifies the set of ratio/interval and/or nominal variables that most accurately predicts group membership in a model with two ratio/interval and/or nominal dependent variables

canonical analysis

group of related codes

category

exposure that has been scientifically tested and shown to occur before the disease outcome and to contribute directly to its occurrence

causal factor

relationship in which an exposure directly causes an outcome

causation

identifies groups of similar observations using an algorithm that seeks to minimize the variations among observations within each group

cluster analysis

label attached to a word or phrase

code

use of words or short phrases to briefly summarize the contents, attitudes, processes, or other aspects of each item in a transcript or other qualitative document

coding/indexing

mathematical model in which each "individual" in the stimulated population exists in only one of several states at one time, but over time these individuals can move between states

compartmental model

probability of an event occurring given that some prior event has already occurred

conditional probability

indicator of neutrality that is present when the results of a study are shown not to be due to researcher bias

confirmability

third variable that is associated with both the exposure variable and the outcome variable and distorts the apparent relationship between the exposure and outcome

confounder

process in which qualitative data are collected and analyzed simultaneously, rather than waiting to begin analysis after all data have been gathered

constant comparison

process of categorizing textual data

content analysis

economic analysis that compares the health gains from an intervention to the financial costs of that intervention

cost effectiveness analysis (CEA)

present when the interpretation of the data accurately reflects the studied groups or texts

credibility

probability of an event occurring by the end of a particular observation period

cumulative probability

refers to raw or unprocessed facts, figures, symbols, or signs

data

interdisciplinary field that uses statistics, machine learning, and other types of computational tools to generate information and knowledge from various types of data

data science

makes logical inferences based on facts or widely accepted premises, and the conclusions are assumed to be certain

deduction

indicator of consistency that is demonstrated through transparency about data collection, analysis, and interpretation methods

dependability

variable in a statistical model that represents the output or outcome for which the variation is being studied

dependent/outcome variable

one in which the outcomes of the model are the same every time the model is run with the same inputs

deterministic model

burden of disease metric that is quantified as the sum of YLDs and YLLs in a population

disability adjusted life year (DALY)

uses the tools of linguistics to evaluate the ordinary use of written and spoken language

discourse analysis

statistical method that identifies the set of ratio/interval and/or nominal variables that most accurately predicts group membership in a model with a nominal dependent variable

discriminant analysis/discriminant function analysis

ability of a model to distinguish between independent groups

discrimination

derived variables created by recoding one variable with n categorical responses into a set of n - 1 dichotomous (0/1) variables

dummy variables

third variable that defines groups of individuals who experience different biological responses to various exposures

effect modifier

represent the proportion of variance accounted for by the correlation between each pair of canonical variates

eigenvalues

concepts that are identified during the early stages of qualitative analysis and assigned a label or code that describes them

emergent codes

cause of a disease or other health disorder

etiology

third variable that produces an apparent but false association between two other variables that are not causally related

extraneous variable

seeks to identify the most frequent and important categories

focused coding

instructs the computer to add the best predictor variables to the model one at a time until adding an additional variable does not significantly improve the overall fit of the model

forward stepwise method

approach to probability that is based on the expected frequency of an event occurring over a long time period or if an occurring over a long time period or if an experiment is repeated many times

frequentist

examines how well real data match the values predicted by a model

goodness of fit test

equation describing the conditional probability of an individual having an event at a particular time given that the person has survived to that time

hazard function

compares durations of time to an event in two populations

hazard ratio

study of the interpretation of texts

hermeneutics

heterogeneity of variance among the variables in a linear regression model that is demonstrated when the distribution of residuals from a regression model across the length of the best fit line is uneven

heteroscedasticity

multivariable regression model that adjusts for different levels of exposure, such as for both census tract and county

hierarchical model/multilevel model

homogeneity of variance among the variables in a linear regression model that is demonstrated by the even distribution of residuals from a regression model across the length of the best fit line

homoscedasticity

variable in a statistical model that predicts the value of some outcome variable

independent/predictor variable

variable used to measure performance, achievement, or change

indicator

makes inferences based on observations, and the conclusions are assumed to be likely

induction

refers to data that have been processed and presented in a format usable for understanding a situation and making decisions

information

occurs when the effect of one predictor variable on an outcome variable depends on the presence or absence of a second predictor variable

interaction

describes a repetitive process

iteration

occurs when a screening test that enables early detection of an adverse health condition is incorrectly interpreted as prolonging survival with the condition

lead time bias

actuarial table that displays conditional and cumulative survival probability in a population

life table

model is used when the outcome variable is a ratio or interval variable

linear regression

statistical test that determines whether survival rates are longer in one population than another

log rank test

visualization of the hypothesized causal pathways that lead to an outcome of interest

logic model

model is a probability based regression model used when the outcome variable is binomial

logistic regression

model that uses a logit link function of ln(p/1-p), also written as logit(p), as their outcome

logit regression

third variable that was not measured in a study but is affecting the apparent association between an exposure variable and an outcome variable

lurking variable

method of data analysis derived from artificial intelligence

machine learning

value of a coefficient in a logistic regression model that gives the model the greatest probability of matching the observed data

maximum likelihood estimate (MLE)

documenting personal reflections an impressions about observations, participants, experiences, codes, categories, and themes

memoing

composite indicator derived from two or more other measures

metric

causal pathway in which many different risk factors or combinations of risk factors contribute to a disease occurring

multicausality

problem that occurs when two or more predictor variables in a multiple regression model are highly correlated, and that redundancy makes the coefficients for one or more of those variables highly inaccurate

multicollinearity

model examines the relationships between several ratio/interval and/or nominal predictor variables and one ratio/interval outcome variable when there is a linear relationship between the independent and dependent variables

multiple linear regression model

examines the relationships between several ratio/interval and/or nominal predictor variables and the value of one nominal outcome variable

multiple logistic regression

qualitative analysis method that seeks to understand personal stories

narrative analysis

machine learning algorithm that is used in the analysis of qualitative and social media data to examine how people speak and write in real life situations

natural language processing

assumes that causal pathways can be bidirectional

nonrecursive model

equation that includes one or more functions of one independent variable along with the derivatives of those functions

ordinary differential equation (ODE)

linear regression modeling approach that finds the line that minimizes the average vertical distance from each point in a data set to the fitted line

ordinary least squares (OLS)

recursive causal analysis strategy that uses regression models to examine causal patterns among variables

path analysis

seeks to group codes into a limited number of categories

pattern coding

predicts the probability group membership while adjusting for covariates

propensity score matching

metric used in health economics to estimate the additional duration of life and quality of life conferred to populations by successful public health interventions

quality adjusted life year (QALY)

construct that captures an individual's perceived position in life in the context of that person's expectations, goals, values, and concerns

quality of life (QOL)

assumes that all causal pathways are undirection

recursive model

statistical model that seeks to understand the relationship between one or more independent variables and one dependent variable

regression model

the difference between the observed value in a data set and the value predicted by a regression model

residual

study of sign and symbols

semiotics

the process of examining the robustness of statistical methods and the results of models

sensitivity analysis

examines whether there is a linear relationship between one ratio or interval predictor variable and one ratio or interval outcome variable

simple linear regression model

process of compiling and analyzing data from social networking services like instagram and twitter

social media analytics

describes results that are false or invalid, such as the spurious associations that are generated by extraneous variables

spurious

the inputs vary according to a probability distribution, so the outcomes differ slightly every time the model is run

stochastic model

nonrecursive causal analysis strategy that can be used to examine complexities in the directionalities of the path diagram

structural equation modeling

statistical evaluation of the distribution of the durations of time that individuals in a study population experience from an initial time point until some well defined event, such as death, discharge from a hospital, or some other outcome

survival analysis

describes the timing of events

temporality

concept that encompasses one or several categories

theme

construct that provides a systematic explanation about phenomenon

theory

variable that is associated with an exposure variable and an outcome variable but is not part of the causal pathway from an exposure to an outcome

third variable

inverse of the variance inflation factor (1/VIF), should not be too close to 0

tolerance

present when the interpretation of qualitative data is likely to be applicable in other circumstances

transferability

should be small enough (typically < 10) to show that the independent variables in a regression model have reasonably independent errors and are not intercorrelated (values cannot be lower than 1)

variance inflation factor (VIF)

burden of disease metric used to quantify the population level reduction in health status attributable to nonfatal conditions

years lived with disability (YLDs)

burden of disease metric used to quantify the population level reduction in health status due to premature mortality

years of life lost (YLLs)