Glossary

(extended from Dul & Hak (2008))

Absolute inefficiency. The total area of the scope where the necessary condition does not constrain the outcome and the outcome is not constrained by the necessary condition. Also see Relative inefficiency, Condition inefficiency, Outcome inefficiency.

Accuracy. See Ceiling accuracy, p value accuracy.

Analytical generalization. The statement that the results from a specific study also apply to a wider part of the theoretical domain based on theoretical analysis and reasoning. Also see Statistical generalization.

Approximate permutation test. A statistical significance test in that produces an estimate of the p value by randomly selecting a large sample from all possible values of the effect size under rearrangements of the labels of the cases in order to approximate the distribution of the effect size under the null hypothesis. Also see Permutation test.

Binary logic. Two valued logic where statements can only be true or false. Also see Conditional logic, Causal logic, Necessity logic, Sufficiency logic.

Bivariate analysis. A statistical analysis with two variables. Also see Multiple bivariate analysis.

Bottleneck table. A tabular representation of the ceiling line showing which values of the condition(s) is/are necessary for a given value of the outcome Y. Also see Ceiling line.

Boolean logic. See Binary logic.

c-accuracy. See Ceiling accuracy.

C-LP. A straight ceiling line based on linear programming. Also see Ceiling line, CR-FDH, CE-FDH.

Case. An instance of a focal unit. Also see Focal unit.

Case selection. The selection of one or a small number of cases from a set of cases for inclusion in a small N study. Also see Small N study, Sampling.

Case study. A research strategy in which one or a small number of cases is selected for a small N observational study. Also see Survey, Experiment.

Causal logic. The logic in which statements are causal relations. Also see Binary logic, Conditional logic, Necessity logic, Sufficiency logic.

Causal relation. A relation between two variable characteristics X and Y of a focal unit in which a value of X (or its change) permits, or results in a value of Y (or in its change). Also see Cause.

Cause. A variable characteristic X of a focal unit of which the value (or its change) permits, or results in a value (or its change) of another variable characteristic Y. Also see Necessary cause, Sufficient cause.

CE-FDH. A step function ceiling line based on the free disposal hull. Also see Ceiling line, CR-FDH, C-LP.

Ceiling accuracy. The extent to which cases are on or below the ceiling line expressed as percentage of the total number of cases.

Ceiling Envelopment - Free Disposal Hull. See CE-FDH.

Ceiling line. The borderline in an XY scatter plot or XY contingency table between the space (virtually) without cases and the space with cases. Also see CE-FDH, CR-FDH, C-LP.

Ceiling Regression - Free Disposal Hull. See CR-FDH.

Ceiling zone. The (virtually) empty space above the ceiling line.

Concept. The variable aspect of a focal unit of a proposition. Also see Independent concept, Dependent concept, Variable.

Conceptual model. A visual representation of a proposition or hypothesis in which the concepts or variables are presented by blocks and the relation between them by an arrow. The arrow originates in the independent concept/variable and points to the dependent concept/variable.

Condition. A variable characteristic X of a focal unit of which the value (or its change) permits, or results in a value (or its change) of another variable characteristic Y (which is called the outcome).
Also see Necessary condition, Sufficient condition, Independent concept, Independent variable, Outcome.

Conditional logic. If-then statements that can only be true or false. Also see Binary logic.

Condition inefficiency. The area of the scope where the condition does not constrain the outcome. Also see Absolute inefficiency, Relative inefficiency, Outcome inefficiency.

Contingency table. A matrix representation of the relation between condition and outcome with the number of cases shown in the cells. Also see Scatter plot.

Continuous necessary condition. A necessary condition in which the condition and the outcome can have infinite numbers of levels (values). Also see Dichotomous necessary condition, Discrete necessary condition.

Control variable. A variable that is added in regression based data analyses for improving the prediction of the outcome and avoiding biased estimation of regression coefficients. Also see Independent variable, Dependent variable.

Convenience sample. A non-probability sample in which the instances are selected for convenience of the researcher. Also see Probability sample, Random sample.

CR-FDH. A straight ceiling line based on a trend line through the upper left peers of the free disposal hull. Also see CE-FDH, C-LP.

d. See Effect size.

Data. Recordings of evidence generated in the process of data collection. Also see Measurement, Qualitative data, Quantitative data, Longitudinal data.

Data analysis. The interpretation of scores obtained in a study in order to generate the result of the study. Also see Qualitative data analysis, Quantitative data analysis, Longitudinal data analysis.

Data collection. The process of identifying and selecting one or more objects of measurement, extracting evidence of the value of the relevant variable characteristics from these objects, and recording this evidence. Also see Object of measurement.

Dataset. A collection of scores obtained from data collection.

Dependent concept. A variable characteristic Y of a focal unit of a proposition of which the value (or its change) is the result of, or is permitted by a value (or its change) of another variable characteristic X (which is called the independent concept). Also see Independent concept.

Dependent variable. A variable characteristic Y of a focal unit of a hypothesis of which the value (or its change) is the result of, or is permitted by a value (or its change) of another variable characteristic X (which is called the independent concept). Also see Independent variable.

Deterministic view. A position taken by the researcher that a condition can only be called a necessary condition for an outcome when there are not exceptions. Also see Probabilistic view.

Dichotomous necessary condition. A necessary condition in which the condition and the outcome can have only two levels (values). Also see Discrete necessary condition, Continuous necessary condition.

Discrete necessary condition. A necessary condition in which the condition and the outcome can have finite numbers of levels (values). Also see Dichotomous necessary condition, Continuous necessary condition.

Domain. See Theoretical domain.

Effect size. The magnitude of the constraint that a necessary condition poses on the outcome expressed as the size of the ceiling zone relative to the size of the scope.

Effect size threshold. The d value selected by the researcher for evaluating the necessary condition hypothesis. Also see Statistical significance threshold.

Empirical Scope. The area of a contingency table or a scatter plot defined by the empirically observed minimum and maximum values of the condition and the outcome. Also see Theoretical scope.

Expected pattern. A score or a combination of scores that is predicted by a hypothesis. Also see Observed pattern, Pattern matching.

Experiment. A research strategy in which the independent variable is manipulated and the dependent variable is measured. Also see Case study, Survey.

Falsification. The view that theories and hypotheses cannot be proven true, but can only be proven false.

Fit. The effect size of a selected ceiling line as percentage of the effect size of the CE-FDH ceiling line.

Focal unit. The stable characteristic of a theory, proposition or hypothesis. Examples are ‘employee,’ ‘team,’ ‘company,’ ‘country.’ Also see Theoretical domain.

Generalization. The statement that the research results from a specific study also apply to a wider part of the theoretical domain. Also see Analytical generalization, Statistical generalization.

Hypothesis. A theoretical statement about the relationship between variables. Also see Necessary condition hypothesis, Proposition.

Independent concept. A variable characteristic X of the focal unit of a proposition, of which the value (or its change) permits, or results in a value (or its change) of another variable characteristic Y (which is called the dependent concept). Also see Dependent concept.

Independent variable. A variable characteristic X of the focal unit of a hypothesis, of which the value (or its change) permits, or results in a value (or its change) of another variable characteristic Y (which is called the dependent variable). Also see Dependent variable.

Influential case. A case that has a large influence on the necessity effect size when removed. Also see Outlier.

Informant. A person who is the object of measurement for a variable and who is knowledgable about that variable and informs the researcher about it. Also see Subject.

Instance of a focal unit. One occurrence of the focal unit.

Large N study. A study with a large number of cases. N stands for the number of cases. Also see Small N study.

Likert scale. A rating scale in the format of a limited number of points that can represent a person’s response. Also see Informant, Subject.

Logic. See Binary logic, Causal logic, Conditional logic, Necessity logic, Sufficiency logic.

Longitudinal data. Scores of variables that are measured at several moments in time. Also see Panel data, Time-series data, Qualitative data, Qualitative data.

Longitudinal data analysis. Evaluating the time pattern of longitudinal data. Also see Qualitative data analysis, Quantitative data analysis.

Measurement. The process in which scores are generated for data analysis. Also see Data, Measurement validity, Measurement reliability.

Measurement validity. The extent to which procedures of data collection and of scoring can be considered to meaningfully capture the ideas contained in the concept of which the value is measured. Also see Measurement reliability*.

Measurement reliability. The degree of precision of a score when the measurement is repeated. Also see Measurement validity.

Mediator. A concept or variable that links the independent and the dependent concept or variable in a proposition or hypothesis.

Moderator. A concept or variable that that qualifies the relation between the independent and the dependent concepts or variables in a proposition or hypothesis.

Multiple bivariate analysis. A series of bivariate analyses.

Multiple regression. A techniques for modelling and analysing the relationship between several independent variables and an dependent variable to understand how a dependent variable changes on average when the independent variables change. Also see OLS regression.

NCA. See Necessary Condition Analysis.

NCA parameters. A set of quantities to evaluate a necessary condition. Also see Scope, Ceiling zone, Effect size, Accuracy, Fit, Ceiling line, Absolute inefficiency, Relative inefficiency, Condition inefficiency, Outcome inefficiency.

Necessary cause. See Necessary condition.

Necessary condition. A cause that must exist in order for the outcome to exist. Also see Sufficient condition.

Necessary Condition Analysis (NCA). An approach and technique for modelling and analysing necessity relations between concepts.

Necessary condition hypothesis. A theoretical statement about the necessity relationship between variables.

Necessary condition in kind. A necessary condition that is qualitatively formulated as ‘X is necessary for Y.’ Also see Necessary condition in degree.

Necessary condition in degree. A necessary condition that is quantitative formulated as ‘level Xc is necessary for level Yc.’ Also see Necessary condition in kind.

Necessity logic. A causal logic in which the cause is a necessary condition. Also see Sufficiency logic, Boolean logic, Binary logic.

Necessity relation. A causal relationship in which the cause is a necessary condition. Also see Sufficiency relation.

Object of measurement. An object that must be observed in order to extract evidence of the value of a variable (data).

Observational study. A research strategy in which variables in the real life context are not manipulated by the researcher. Also see Case study, Survey, Experiment.

Observed pattern. The score or the combination of scores obtained in a study. In data analysis, an observed pattern is compared (“matched”) with an expected pattern. Also see Expected pattern, Pattern matching.

OLS regression. A techniques for modelling and analysing the relationship between one or more independent variables and an dependent variable to understand how a dependent variable changes on average when the independent variables change, based on the Ordinary Least Squares estimation technique where the squared vertical distances between the cases and the regression line is minimized. Also see Multiple regression.

Omitted variable bias. The estimation error that is made when a variable is omitted from a conceptual model that is analysed statistically.

Outcome. The variable characteristic Y of a focal unit of which the value (or its change) is the result of, or is permitted by a value (or its change) of another variable characteristic X (which is called the condition). Also see Dependent concept, Dependent variable, Condition.

Outcome inefficiency. The area of the scope where the outcome is not constrained by the condition. Also see Absolute inefficiency, Relative inefficiency, Condition inefficiency.

Outlier. An outlier is a point (case) in a scatter plot or contingency table that is considered to be ‘far away’ from the other points (cases). Also see Influential case.

p-accuracy. See p value accuracy.

Panel data. See Longitudinal data.

Pattern. See Expected pattern, Observed pattern.

Pattern matching. Comparing two or more patterns in order to determine whether patterns match (i.e. that they are the same) or do not match (i.e. that they differ). Pattern matching in data analysis is comparing an observed pattern with an expected pattern.

Peer. A case that is used to draw the ceiling line.

Permutation test. A statistical significance test that produces an exact p value by obtaining the distribution of the effect size under the null hypothesis by calculating all possible values of the effect size under rearrangements of the labels of the cases. Also see Approximate permutation test.

Probabilistic view. A position taken by the researcher that a condition can also be called a necessary condition for an outcome when there are a few exceptions.

p value. The probability that the effect size is greater than or equal to the observed effect size when the null hypothesis that the variables are unrelated is true.

p value accuracy. The estimated difference between the exact p value of the effect size and the estimated p value of the effect size. Also see Approximate permutation test, Permutation test.

Population. The set of instances of a focal unit defined by one or a small number of criteria.

Probability sample. A sample in which each instance of a sampling frame has a known non-zero probability of being selected into the sample. Also see Convenience sample, Random sample.

Proposition. A theoretical statement about the relationship between concepts. Also see Hypothesis.

QCA. See Qualitative Comparative Analysis.

Qualitative data. Scores expressed in words or letters. Also see Quantitative data, Longitudinal data.

Qualitative Comparative Analysis (QCA). An approach and technique for modelling and analysing the relationship between concepts and combinations of concepts by using binary logic.

Qualitative data analysis. Identifying and evaluating a pattern in the scores obtained in a study by visual inspection. Also see Pattern matching, Visual inspection, Quantitative data analysis, Longitudinal data analysis.

Quantitative data. Scores expressed in numbers. Also see Qualitative data, Longitudinal data.

Quantitative data analysis. Generating and evaluating the output of statistical procedures applied to the scores obtained in a study. Also see Pattern matching, Qualitative data analysis, Longitudinal data analysis.

Random sample. A probability sample in which each instance of the sampling frame has the same probability of being selected into the sample. Also see Probability sample, Convenience sample.

Rating scale. A method in which a person assigns a value to an object. Also see Informant, Subject.

Regression. See OLS regression, Multiple regression.

Rejection. A hypothesis is said to be rejected if the observed pattern of scores is not the same as the pattern predicted by the hypothesis. Also see Expected pattern, Observed pattern, Pattern matching.

Relative inefficiency. The total area of the scope where the necessary condition does not constrain the outcome and the outcome is not constrained by the necessary condition, expressed as percentage of the scope. Also see Absolute inefficiency, Condition inefficiency, Outcome inefficiency.

Replication. Conducting a test of a hypothesis in another instance, or in another group or population of instances of the focal unit.

Research strategy. See Research design.

Research design. A category of procedures for selecting or generating one or more instances of a focal unit as well as for analysing the data that are observed or generated in the selected or generated instance or instances. Also see Experiment, Survey, Case study.

Sample. A set of instances selected from a population or a theoretical domain. Also see Convenience sample, Probability sample, Random sample.

Sampling. The selection of instances from a population or a theoretical domain. Also see Sample, Sampling frame.

Sampling frame. A list of all instances of a population. Also see Probability sampling, Population.

Scatter plot. A graphical representation of the relation between condition and outcome on two axes with cases shown as points. Also see Contingency table.

Scope. The area of a contingency table or a scatter plot defined by the minimum and maximum values of the condition and the outcome. Also see Empirical scope, Theoretical scope.

Score. A value assigned to a variable based on data.

Significance. See Statistical significance, Substantive significance.

Small N study. A study with one or a small number of cases. N stands for the number of cases. Also see Large N study.

Statistical generalization. The statement that the research results that are obtained in a sample of a population also apply to the population from which the sample is drawn. Also Analytical generalization.

Statistical significance. The meaningfulness of the effect size from a statistical perspective. Also see p value, Substantive significance.

Statistical significance threshold. The p value selected by the researcher for evaluating the necessary condition hypothesis. Also see Effect size threshold.

Study. A research project in which a research objective is formulated and achieved.

Subject. A person who is the object of measurement and an instance of the focal unit of the theory. Also see Informant.

Substantive significance. The meaningfulness of the effect size from a practical perspective. Also see Statistical significance.

Sufficiency logic. A causal logic in which the cause is a sufficient condition. Also see Necessity logic.

Sufficiency relation. A causal relationship in which the cause is a sufficient condition. Also see Necessity relation.

Sufficient cause. See Sufficient condition.

Sufficient condition. A cause that always results in an outcome. Also see Necessary condition.

Survey. A research strategy in which a single population of instances of the focal unit is selected for a large N observational study. Also see Case study, Experiment.

Test. Determining whether a hypothesis is supported or rejected in an instance or in a group or population of instances selected from the theoretical domain.

Theoretical domain. The universe of instances of a focal unit of a theory, proposition or hypothesis where the theory, proposition or hypothesis is supposed to hold.

Theoretical scope. The area of a contingency table or a scatter plot defined by the theoretically possible minimum and maximum values of the condition and the outcome. Also see Empirical scope.

Theory. A set of propositions regarding the relations between the variable characteristics (concepts) of a focal unit, and the description why the relations exist.

Theory-in-use. A more or less consistent set of beliefs in practice about the world.

Time-series data. Scores of a single variables that is measured at many moments in time. Also see Longitudinal data, Panel data, Qualitative data, Qualitative data.

Time-series data analysis. Evaluating the time pattern of time-series data. Also see Longitudinal data analysis, Qualitative data analysis, Quantitative data analysis.

Variable. The variable aspect of a focal unit of a hypothesis. Also see Concept, Independent variable, Dependent variable.

Visual inspection. The procedure by which patterns are discovered or compared by looking at the scores or a graphical representation of the scores. Also see Pattern matching, Qualitative data analysis.

References

Dul, J., & Hak, T. (2008). Case study methodology in business research. Routledge. https://www.routledge.com/Case-Study-Methodology-in-Business-Research/Dul-Hak/p/book/9780750681964