Knowledgebase
Question Last Updated on: 2/6/2025
This article explains the settings of LXEdge. To open the settings page, click on the gear at the bottom left of the LXEdge window.
Audio/Video Settings
This section covers video recording options:
Chart Settings
This section contains settings related to the chart. These are only applied to new PFs. Once a chart is recorded, these settings are locked in that chart and cannot be changed.
Disabling this option removes the response onset window during new chart recordings. Responses will then be indicated solely by a vertical line and the answer on the chart.
Enabling the Multimedia Bar activates a bar that overlays the bottom part of the question bar on charts when multimedia is shown.
Enable this feature to have questions read aloud. It supports Microsoft Windows TTS (Speech Application Program Interface or SAPI) voices.
Display Scoresheet: Enables showing the scoresheet on the chart once recording has ended.
Allows the use of annotations during chart recording. You can modify the ID and description of each annotation as desired.
Hotkey Settings
This section allows you to set up keyboard shortcuts (hotkeys) for controlling LXEdge. Click any box to change the key assigned to each action. Using the keyboard instead of the mouse can provide quicker control of the application.
Scoring Settings
Allows the examiner to select from ESS, three position and seven position scoring.
Refers to the type of numerical scale used to obtain the scores assigned to the Relevant Questions. Manual scores can be thought of as either multinomial or Likert type.
ESS: ESS scores are 3 position multinomial scores with weighted EDA values. ESS scores are multinomial because each score can have one of three possible values [-, 0, +]. Scores are assigned to each analysis spot, consisting of a Relevant Question (RQ) and a Comparison Question (CQ), depending on whether the change in physiological activity is objectively greater at the RQ or CQ, or are objectively equivalent. In contrast, when there are two possible outcome values (e.g., [-, +]) these scores would be binomial. ESS scores are weighed because EDA scores can have the integer values [-2, 0, +2] while other sensors are limited to the integer values [-1, 0, +1]. ESS scores are aggregated through summation. A result of these weighted scores is that EDA data contribute more information to test scores and test results. ESS scores are assigned using only the primary scoring features: electrodermal amplitude of increase in phasic activity, cardiovascular amplitude of increase in relative blood pressure, suppression or reduction of respiratory activity, and suppression or reduction of vasomotor activity. ESS scoring features are referred to as Kircher features and have the advantage that they can be quantified objectively.
3-Position: Three-position scores are unweighted integer scores [-1, 0, +1] for all polygraph recording sensors. These scores indicate whether a greater change in physiology is observed in response to the RQ or CQ within an analysis spot. Three position scores can be multinomial when the difference is based on objective data using primary response features, referred to as Kircher features. Three position scores can also be obtained as Likert scores, such as when using the Federal 3-Position method which involves a combination of primary and secondary features. In contrast to the objective quantification of primary response features, secondary features can involve pattern recognition methods that are less easily subject to quantification, and which therefor involve a greater degree of subjectivity - along with greater potential for inter-scorer variability. Although superficially like multinomial scores, Likert scores were devised to obtain numerical values for subjective information.
7-Position: Seven-position scores are unweighted integer scores [-3, -2, -1, 0, +1, +2, +3] for all polygraph recording sensors. Seven-position scores attempt to capture more information than three-position scores by representing the degree of difference in addition to whether the greater change in physiological activity was observed at the RQ or CQ within each analysis spot. Seven-position scores are Likert type values representative of subjective judgments - with no theoretical basis (subject to mathematical and logical proof) for the locations of boundary or threshold differences between the seven-position integer scores [-3, -2, -1, 0, +1, +2, +3], despite the formulation of arbitrary or empirical rules and procedures to define these differences. Several different seven-position scoring methods have been described over many decades. Emphasis on evidence-based practice has resulted in obvious practical and empirical similarities between some seven-position scoring methods - especially those published by ASTM, the researchers at the University of Utah, and U.S. Federal polygraph programs. Seven-position scores are obtained using a combination of primary and secondary scoring features. In contrast to the objective quantification of primary response features, secondary features can involve pattern recognition methods that are less easily subject to quantification, and which therefor involve a greater degree of subjectivity - along with greater potential for inter-scorer variability. Seven-position scores may also be subject to inter-scorer variability associated with the application of different boundary or threshold procedures for the different integer values. In actual field practice the entire range of seven-position scores may be used only very rarely for some sensors (e.g., respiration scores are often constrained to the range [-1, 0, +1]), and this may contribute to some reduction of inter-scorer variability.
Allows examiner to choose statistical cutscores (ESS-M) or traditional cutscores (ESS) for decision reporting.
Numerical cutscores are the information thresholds used to understand the strength and meaning of grand total and subtotal scores, and to classify polygraph test results as either deceptive or truthful.
Statistical: Statistical cutscores are obtained through the computation of a statistical reference model. This model might be a simple table of all possible score values and the probabilities associated with each, and might also take the form of a mathematical/statistical function to compute a reference table. ESS cutscores were obtained using both empirical and mathematical/theoretical methods. Statistical reference models are used to select cutscores to optimize desired effect sizes that relate to organizational goals and mission objectives. Statistical cutscores are selected to provide a basis for discussion of the probabilistic strength and meaning of categorical polygraph test results. Statistical cutscores also include the use of statistical corrections to reduce the effects of multiplicity error when using subtotal scores. ESS cutscores are selected to attain posterior information that exceeds the strength of prior information at a required level of statistical significance. Published statistical reference models are available for ESS, 3-Position, and 7-Position scores.
Traditional: Traditional cutscores do not include the use of statistical corrections, and were selected using heuristic methods that do not involve the use of empirical or statistical reference distributions. These cutscores are associated with each different test format, and are traditionally used with 3-Position and 7-Position scoring methods.
Allows the examiner to choose Simple Cut Scores (the default and preferred method) or to allow non-simple cutscores to determine outcome. Examiners should only turn this off if they are familiar with the non-simple cutscore paradigm.
The default is 0.5 but examiners can adjust the prior that is used to condition the test score to calculate the posterior probability or odds.
Prior odds describe the probabilistic strength of information prior to conducting a polygraph test. The strength of information can is often described in the form of the odds or chances that an examinee is actually deceptive. Odds have the advantages that they express probabilistic information using whole numbers, and explicitly convey that the information describes the strength of a possible outcome compared to the strength of some other possible outcome. Prior information is then conditioned on the probabilistic strength of the information from the test to obtain the posterior odds. Algebraically, because the prior odds convey the strength of information indicative of deception and truth telling, posterior information can also be described as pertaining to deception and truth telling. The default prior is 1 to 1 (.5), indicating that the strength of prior information for the deception and truth-telling is objectively equal. The prior can be changed based on available information.
The default is 0.05 but examiners can adjust alpha based on the customers tolerance for an error.
Alpha indicates the strength of the probabilistic confidence that the posterior odds are stronger than the prior odds, while accounting for expected variation (given a small data set of test scores and the possibility that these scores would vary if the test were repeated). Alpha values are used to select ESS (statistical) cutscores, with the default values at .05 for all outcome classifications (DI, NDI, SR, NSR). ESS alphas indicate the (1-alpha x 100%) range of expected variation that is expected to be observed on repeated tested. This is referred to as a Bayesian credible interval (allegorical to a frequentist confidence interval). Cutscores are selected to ensure that the lower limit of the credible interval for posterior odds exceeds the prior odds. In other words, with alpha = .05 there is a 95% probability that the posterior information is stronger than the prior - that the posterior information would continue to exceed the prior with more data (upon repeated testing). Traditional cutscores are not associated with alpha values.
The default is 1.0 so that when the lower level of the credible interval for a given score surpasses this value, the ESS-M test reporter will provide a recommended decision. Examiners can adjust this based on their customers? desire for the lower level of the credible interval for a given alpha.
The cut ratio is an added level of control when selecting ESS cutscores. The lower limit of the credible interval for the posterior odds must exceed this value. The default cut ratio is 1 to 1, meaning that ESS cutscores will not permit a classification of deception or truth telling when the lower limit is less than this value.
Turns on or off the test of proportions.
The Test of Proportions is a common statistical method used to determine if there are statistically significant imbalances observed proportions when comparing two groups. It is used polygraph data analysis to determine whether observed artifacts (occurring at CQs and RQs) are consistent with a random distribution. When the statistical probability that the artifact pattern is random is very low (exceeds an alpha threshold) it the data can be classified as statistically significant for non-random artifacts, indicating a possibility of strategic or systematic faking (countermeasures) during testing. Test results are inconclusive when the Test of Proportion is statistically significant. Alpha for the Test of Proportion is set to .05. This option enables or disables the Test of Proportions.
Allows DI/SR results to report even when the Test of Proportions is significant.
This option permits the reporting of DI/SR classifications when the Test of Proportions is statistically significant if the test data (test scores) support this classification.
Allows adjusting the alpha for when the Test of Proportions is significant.
Alpha for the Test of Proportions is set by default to .05
This setting will combine upper and lower pneumo scores for one value. For example, if the upper pneumo is a +1 and the lower pneumo is a -1, the inserted pneumo score used for ESS-M calculation will be 0.
Grand Total Rule: The Grand Total Rule (GTR) is used with single-issue exams. RQs for single issue exams are assumed to have a shared source, or cause, of response variance. The GTR is the simplest of all decision rules. However, accuracy effect sizes using the GTR have been among the highest in published polygraph studies. The GTR uses all available recorded data to produce a single classification of the test as a whole. Procedurally, the GTR involves the summation of a grand total using all scores for all RQs and all recording sensors, and the comparison of this grand total with the numerical cutscores for deceptive and truthful classifications. Each RQ inherits the same result as the test as a whole. In other words, RQs are not interpreted or classified differently than the test as a whole.
Subtotal Score Rule: The Subtotal Score Rule (SSR) is a commonly used decision rule for multiple-issue polygraph exams. RQs for multiple-issue polygraph exams are assumed to have independent criterion variance. In practical terms, this means that different RQs describe different behaviors, and it is conceivable that a person may be involved in none, some, or all the behavioral target issues. In scientific terms, an assumption of independence means that there is no shared basis of response among any of the RQs - that each response to each of the RQs is completely unaffected by any of the responses to all the other RQs. Independence is a rigorous concept that can be difficult to attain. An assumption of independence, declared prior to data acquisition and data analysis, can broaden and increase the sensitivity of the polygraph test. However, with the SSR, the use of multiple statistical classifications introduces multiplicity effects that are known to reduce the precision of the test result. Use of statistical corrections - statistically corrected cut scores, or statistically corrected outcome probabilities - can reduce, though does not eliminate, the effects of statistical multiplicity. Traditional cutscores do not involve the use of a statistical correction. ESS cutscores are obtained with a statistical correction for truthful classifications. This reduces the occurrence of inconclusive results among innocent/truthful persons. The ESS does not use a statistical correction for deceptive classifications. Procedurally, the SSR requires the identification of the RQ with lowest numerical subtotal score, and the comparison of this score with numerical cutscores for deceptive and truthful classifications. The overall test result is then inherited from the RQ with the lowest numerical subtotal score. Next, the categorical results are obtained for the other RQ by comparing each remaining subtotal to the numerical cutscores for deception and truth-telling. Importantly, it is not permissible to classify both deception and truth-telling within a multiple-issue polygraph. Whenever any of the RQ subtotals is classified as deceptive all other RQ subtotals that cannot be classified as deceptive are classified as inconclusive or no-opinion. The SSR can be used with either statistical or traditional cutscores.
Two-stage Rule: The Two-stage Rule (TSR) can be thought of as the sequential use of both the GTR and SSR concepts. Stage 1 of the TSR is procedurally similar to the GTR. Subtotal scores are not used during Stage 1. The TSR is complete at Stage 1 if the test result can be classified as deceptive or truthful by comparing the grand total score to the numerical cutscores. Stage 2 is used only when a test cannot be classified as either deceptive or truthful during Stage 1. Stage 2 is somewhat similar to the SSR with the exception that truthful classifications are not made during this stage. Stage 2 requires the comparison of the lowest RQ subtotal score with the numerical cutscore for deceptive classifications using subtotal scores. A test result is inconclusive/no-opinion if the result cannot be classified as either deceptive or truthful at Stage 1 and also cannot be classified as deceptive at Stage 2. Because of the sequential use of the grand total and subtotal scores, the GTR provides a procedural protection against multiplicity effects (inflated alpha) that can occur when using subtotal scores. Multiplicity effects with TSR are most obvious when using traditional cutscores. ESS cutscores are obtained using a statistical correction which also reduces statistical multiplicity error. On rare occasions, when using the TSR, a grand total score may support a truthful classification while the lowest subtotal score supports a deceptive classification. In such cases, when using ESS cutscores it is permissible to classify the test result as deceptive based on the lowest subtotal score regardless of the grand total score, but only if the subtotal cutscore includes a statistical correction for multiplicity. This approach is justified by the presence of unexpected or excessive variability in the test data, which undermines the reliability of conclusions based on the grand total score. When using the TSR, each RQ inherits the same result as the test as a whole. In other words, RQs are not interpreted or classified differently than the test as a whole. The TSR can be used with either traditional or statistical cutscores.
Federal Zone Rule: The Federal Zone Rule (FZR) is traditionally used with the Federal ZCT and Federal You Phase test formats using traditional cutscores. RQs for these formats have a shared source of response variance - a single known or alleged incident - and therefor function as single-issue formats. The FZR involves several comparisons of the grand total and subtotal scores with the numerical cutscores for deception and truth telling. Using the Federal ZCT format the cutscores are [-6, -3, +6/+1]. A test result is classified as deceptive if the grand total score is less than or equal to -6 or if any subtotal score is less than or equal to -3. A test result is classified as truthful if the grand total score is greater than or equal to +6 if all subtotal scores are equal to or greater than +1. Using the Federal YouPhase format the cutscores are [-4, -3, +4/+1]. A test result is classified as deceptive if the grand total score is less than or equal to -4 or if any subtotal score is less than or equal to -3. A test result is classified as truthful if the grand total score is greater than or equal to +4 if all subtotal scores are equal to or greater than +1. The FZR provides increased sensitivity to deception, comp though without management of statistical multiplicity error. When using the FZR each RQ inherits the same result as the test as a whole. In other words, RQs are not interpreted or classified differently than the test as a whole.
TES Rule: The TES Rule (TES) is described in the published studies on TES format that is used in a variety of multiple issue screening contexts. The TES rule uses traditional cutscores and applies the procedures from the FZR to the TES/DLST format. TES cutscores are [-4, -3, +4/+1]. A test result is classified as deceptive if the grand total score is less than or equal to -4 or if any subtotal score is less than or equal to -3. A test result is classified as truthful if the grand total score is greater than or equal to +4 but if all subtotal scores are equal to or greater than +1. Each RQ inherits the same result as the test as a whole. In other words, RQs are not interpreted or classified differently than the test as a whole.
This can be used when the Scoring Rule is 3 or 7 Position and the Decision Rule is Federal Zone Rule.
The DLST Rule (DLST) is described in the published studies on DLST format that is used in a variety of multiple issue screening contexts. The DLST rule uses ESS-M cutscores. DLST cutscores are [-3,+1]. A test result is classified as deceptive if any subtotal score is less than or equal to -3. A test result is classified as truthful if all subtotal scores are equal to or greater than +1. Each RQ inherits the same result as the test as a whole. In other words, RQs are not interpreted or classified differently than the test as a whole.
This is done when Exam Type is Multi Issue Independent and SSR is selected as the Decision Rule when a DLST formatted test has been selected to be scored.
Sensor Settings
Manages the display settings for each sensor (trace) on the chart. All sensors come with options for gain, label, color, and trace thickness. The EDA sensor additionally includes trace mode and EDA mode settings, which are set to Automatic and GSR by default.
System Settings
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