Enum StatisticModelCode

pub enum StatisticModelCode {
    Adjusted,
    Anova,
    AnovaOneWay,
    AnovaThreeWay,
    AnovaTwoWay,
    AnovaTwoWayReplication,
    BinomialDistributionRegression,
    ChiSquareTest,
    ChiSquareTestHomogeneity,
    ChiSquareTestTrend,
    CoxProportionalHazards,
    DersimonianLairdMethod,
    EffectsFixed,
    EffectsRandom,
    EmpiricalBayes,
    FishersExactTest,
    FriedmanTest,
    Glm,
    GlmGeneralizedLogit,
    GlmIdentity,
    GlmLog,
    GlmLogit,
    GlmProbit,
    Glmm,
    GlmmGeneralizedLogit,
    GlmmIdentity,
    GlmmLog,
    GlmmLogit,
    GlmmProbit,
    GoodmanKruskasGamma,
    HartungKnapp,
    HedgesMethod,
    HunterSchmidt,
    InteractionTerm,
    InverseVariance,
    KendallCorrelation,
    KruskalWallisTest,
    LinearRegression,
    LogisticRegression,
    MannWhitneyUTest,
    Manova,
    ManteHaenszelMethod,
    MaximumLikelihood,
    McnemarsTest,
    MetaAnalysis,
    ModifiedHartungKnapp,
    MultinomialDistributionRegression,
    NegativeBinomialRegression,
    OneSampleTTest,
    OneTailedTest,
    PairedTTest,
    PauleMandelMethod,
    PearsonCorrelation,
    PetoMethod,
    PoissonRegression,
    PolynomialRegression,
    PoolGeneralizedLinearMixedModel,
    PoolInverseVariance,
    PoolMantelHaenzsel,
    PoolPeto,
    RestrictedLikelihood,
    SidikJonkman,
    SignTest,
    SpearmanCorrelation,
    TauDersimonianLaird,
    TauEmpiricalBayes,
    TauHedges,
    TauHunterSchmidt,
    TauMaximumLikelihood,
    TauPauleMandel,
    TauRestrictedMaximumLikelihood,
    TauSidikJonkman,
    TwoSampleTTest,
    TwoTailedTest,
    WilcoxonRankSumTest,
    WilcoxonSignedRankTest,
    Ztest,
    ZeroCellConstant,
    ZeroCellContinuityCorrection,
}

StatisticModelCode. The role that the assertion variable plays.

FHIR version: 5.0.0.

Variants

Adjusted

adjusted

Adjusted analysis. Used for adjusted analysis, paired with variable element(s)

Anova

anova

ANOVA (ANalysis Of VAriance). Used for ANOVA method of analysis, may be paired with “value” to express degrees of freedom

AnovaOneWay

anovaOneWay

one-way ANOVA. Used for one-way ANOVA method of analysis, may be paired with “value” to express degrees of freedom

AnovaThreeWay

anovaThreeWay

3-way ANOVA. Used for 3-way ANOVA method of analysis, may be paired with “value” to express degrees of freedom

AnovaTwoWay

anovaTwoWay

2-way ANOVA without replication. Used for 2-way ANOVA without replication method of analysis, may be paired with “value” to express degrees of freedom

AnovaTwoWayReplication

anovaTwoWayReplication

2-way ANOVA with replication. Used for 2-way ANOVA with replication method of analysis, may be paired with “value” to express degrees of freedom

BinomialDistributionRegression

binomialDistributionRegression

Binomial Distribution for Regression. Used for Binomial Distribution for Regression, no additional elements needed

ChiSquareTest

chiSquareTest

Chi-square test. Used for Chi-square test, may be paired with “value” to express degrees of freedom

ChiSquareTestHomogeneity

chiSquareTestHomogeneity

Chi-square test for homogeneity. Used for Chi-square test for homogeneity, may be paired with “value” to express degrees of freedom

ChiSquareTestTrend

chiSquareTestTrend

Chi-square test for trend. Used for Chi-square test for trend, may be paired with “value” to express degrees of freedom

CoxProportionalHazards

coxProportionalHazards

Cox Proportional Hazards. Used for Cox proportional hazards method of analysis, no additional elements needed

DersimonianLairdMethod

dersimonianLairdMethod

Dersimonian-Laird method. Used for Dersimonian-Laird method of tau estimation, no additional elements needed

EffectsFixed

effectsFixed

Fixed-effects. From a fixed-effects analysis, no additional elements needed

EffectsRandom

effectsRandom

Random-effects. From a random-effects analysis, no additional elements needed

EmpiricalBayes

empiricalBayes

Empirical Bayes method. Used for Empirical Bayes method of tau estimation, no additional elements needed

FishersExactTest

fishersExactTest

Fisher’s exact test. Used for Fisher’s exact test, may be paired with “value” to express degrees of freedom

FriedmanTest

friedmanTest

Friedman test. Used for Friedman test, no additional elements needed

Glm

glm

GLM (Generalized Linear Model). Used for GLM (Generalized Linear Model), no additional elements needed

GlmGeneralizedLogit

glmGeneralizedLogit

GLM with generalized logit link. Used for GLM with generalized logit link, no additional elements needed

GlmIdentity

glmIdentity

GLM with identity link. Used for GLM with identity link, no additional elements needed

GlmLog

glmLog

GLM with log link. Used for GLM with log link, no additional elements needed

GlmLogit

glmLogit

GLM with logit link. Used for GLM with logit link, no additional elements needed

GlmProbit

glmProbit

GLM with probit link. Used for GLM with probit link, no additional elements needed

Glmm

glmm

Generalized linear mixed model (GLMM). Used for Generalized linear mixed model (GLMM), no additional elements needed

GlmmGeneralizedLogit

glmmGeneralizedLogit

GLMM with generalized logit link. Used for GLMM with generalized logit link, no additional elements needed

GlmmIdentity

glmmIdentity

GLMM with identity link. Used for GLMM with identity link, no additional elements needed

GlmmLog

glmmLog

GLMM with log link. Used for GLMM with log link, no additional elements needed

GlmmLogit

glmmLogit

GLMM with logit link. Used for GLMM with logit link, no additional elements needed

GlmmProbit

glmmProbit

GLMM with probit link. Used for GLMM with probit link, no additional elements needed

GoodmanKruskasGamma

goodmanKruskasGamma

Goodman Kruska’s Gamma. Used for Goodman Kruska’s Gamma, no additional elements needed

HartungKnapp

hartungKnapp

Hartung-Knapp adjustment. Hartung-Knapp/Hartung-Knapp-Sidik-Jonkman adjustment used in meta-analysis, no additional elements needed

HedgesMethod

hedgesMethod

Hedges method. Used for Hedges method of tau estimation, no additional elements needed

HunterSchmidt

hunterSchmidt

Hunter-Schmidt method. Used for Hunter-Schmidt method of tau estimation, no additional elements needed

InteractionTerm

interactionTerm

Interaction term. Used for interaction term, paired with “value” and two or more variable elements

InverseVariance

inverseVariance

Inverse variance method. Used for inverse variance method of meta-analysis, no additional elements needed

KendallCorrelation

kendallCorrelation

Kendall correlation. Used for Kendall correlation, no additional elements needed

KruskalWallisTest

kruskalWallisTest

Kruskal Wallis test. Used for Kruskal Wallis test, may be paired with “value” to express degrees of freedom

LinearRegression

linearRegression

Linear Regression. Used for linear regression method of analysis, no additional elements needed

LogisticRegression

logisticRegression

Logistic Regression. Used for logistic regression method of analysis, no additional elements needed

MannWhitneyUTest

mannWhitneyUTest

Mann-Whitney U test. Used for Mann-Whitney U test, no additional elements needed

Manova

manova

multivariate ANOVA (MANOVA). Used for multivariate ANOVA (MANOVA) method of analysis, may be paired with “value” to express degrees of freedom

ManteHaenszelMethod

manteHaenszelMethod

Mantel-Haenszel method. Used for Mantel-Haenszel method, no additional elements needed

MaximumLikelihood

maximumLikelihood

Maximum Likelihood method. Used for Maximum Likelihood method of tau estimation, no additional elements needed

McnemarsTest

mcnemarsTest

McNemar’s test. Used for McNemar’s test, no additional elements needed

MetaAnalysis

metaAnalysis

Meta-analysis. Used for meta-analysis, no additional elements needed

ModifiedHartungKnapp

modifiedHartungKnapp

Modified Hartung-Knapp adjustment. Modified Hartung-Knapp/Hartung-Knapp-Sidik-Jonkman adjustment used in meta-analysis, no additional elements needed

MultinomialDistributionRegression

multinomialDistributionRegression

Multinomial Distribution for Regression. Used for Multinomial Distribution for Regression, no additional elements needed

NegativeBinomialRegression

negativeBinomialRegression

Negative Binomial Regression. Used for Negative Binomial Regression, no additional elements needed

OneSampleTTest

oneSampleTTest

1-sample t-test. Used for 1-sample t-test, may be paired with “value” to express degrees of freedom

OneTailedTest

oneTailedTest

one-tailed test (1 threshold). Used for one-tailed test (1 threshold), no additional elements needed

PairedTTest

pairedTTest

paired t-test. Used for paired t-test, may be paired with “value” to express degrees of freedom

PauleMandelMethod

pauleMandelMethod

Paule-Mandel method. Used for Paule-Mandel method of tau estimation, no additional elements needed

PearsonCorrelation

pearsonCorrelation

Pearson correlation. Used for Pearson correlation, no additional elements needed

PetoMethod

petoMethod

Peto method. Used for Peto method of meta-analysis, no additional elements needed

PoissonRegression

poissonRegression

Poisson Regression. Used for Poisson Regression, no additional elements needed

PolynomialRegression

polynomialRegression

Polynomial Regression. Used for Polynomial regression method of analysis, no additional elements needed

PoolGeneralizedLinearMixedModel

poolGeneralizedLinearMixedModel

Generalized linear mixed model (GLMM). Generalized linear mixed model (GLMM) method for pooling in meta-analysis

PoolInverseVariance

poolInverseVariance

Inverse variance method. Inverse variance method for pooling in meta-analysis

PoolMantelHaenzsel

poolMantelHaenzsel

Mantel-Haenszel method. Mantel-Haenszel method for pooling in meta-analysis

PoolPeto

poolPeto

Peto method. Peto method for pooling in meta-analysis

RestrictedLikelihood

restrictedLikelihood

Restricted Maximum Likelihood method. Used for Restricted Maximum Likelihood method of tau estimation, no additional elements needed

SidikJonkman

sidikJonkman

Sidik-Jonkman method. Used for Sidik-Jonkman method of tau estimation, no additional elements needed

SignTest

signTest

sign test. Used for sign test, no additional elements needed

SpearmanCorrelation

spearmanCorrelation

Spearman correlation. Used for Spearman correlation, no additional elements needed

TauDersimonianLaird

tauDersimonianLaird

Dersimonian-Laird method. Dersimonian-Laird method for tau squared

TauEmpiricalBayes

tauEmpiricalBayes

Empirical Bayes method. Empirical Bayes method for tau squared

TauHedges

tauHedges

Hedges method. Hedges method for tau squared

TauHunterSchmidt

tauHunterSchmidt

Hunter-Schmidt method. Hunter-Schmidt method for tau squared

TauMaximumLikelihood

tauMaximumLikelihood

Maximum Likelihood method. Maximum Likelihood method for tau squared

TauPauleMandel

tauPauleMandel

Paule-Mandel method. Paule-Mandel method for tau squared

TauRestrictedMaximumLikelihood

tauRestrictedMaximumLikelihood

Restricted Maximum Likelihood method. Restricted Maximum Likelihood method for tau squared

TauSidikJonkman

tauSidikJonkman

Sidik-Jonkman method. Sidik-Jonkman method for tau squared

TwoSampleTTest

twoSampleTTest

2-sample t-test. Used for 2-sample t-test, may be paired with “value” to express degrees of freedom

TwoTailedTest

twoTailedTest

two-tailed test (2 thresholds). Used for two-tailed test (2 threshold), no additional elements needed

WilcoxonRankSumTest

wilcoxonRankSumTest

Wilcoxon rank-sum test. Used for Wilcoxon rank-sum test, no additional elements needed

WilcoxonSignedRankTest

wilcoxonSignedRankTest

Wilcoxon signed-rank test. Used for Wilcoxon signed-rank test, no additional elements needed

Ztest

zTest

z-test. Used for z-test, no additional elements needed

ZeroCellConstant

zeroCellConstant

Zero-cell adjustment with constant. Zero-cell adjustment done by adding a constant to all cells of affected studies, paired with “value” to define the constant

ZeroCellContinuityCorrection

zeroCellContinuityCorrection

Zero-cell adjustment with continuity correction. Zero-cell adjustment done by treatment arm continuity correction, no additional elements needed

Trait Implementations

impl AsRef<str> for StatisticModelCode

fn as_ref(&self) -> &str

Converts this type into a shared reference of the (usually inferred) input type.

impl Clone for StatisticModelCode

fn clone(&self) -> StatisticModelCode

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for StatisticModelCode

fn fmt(&self, f: &mut Formatter<'_>) -> Result<(), Error>

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for StatisticModelCode

fn deserialize<D>( deserializer: D, ) -> Result<StatisticModelCode, <D as Deserializer<'de>>::Error>

where D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Display for StatisticModelCode

fn fmt(&self, f: &mut Formatter<'_>) -> Result<(), Error>

Formats the value using the given formatter.

impl From<StatisticModelCode> for CodeableConcept

fn from(code: StatisticModelCode) -> CodeableConcept

Converts to this type from the input type.

impl From<StatisticModelCode> for Coding

fn from(code: StatisticModelCode) -> Coding

Converts to this type from the input type.

impl FromStr for StatisticModelCode

type Err = String

The associated error which can be returned from parsing.

fn from_str( s: &str, ) -> Result<StatisticModelCode, <StatisticModelCode as FromStr>::Err>

Parses a string s to return a value of this type.

impl Hash for StatisticModelCode

fn hash<__H>(&self, state: &mut __H)

where __H: Hasher,

Feeds this value into the given Hasher.

fn hash_slice<H>(data: &[Self], state: &mut H)

where H: Hasher, Self: Sized,

Feeds a slice of this type into the given Hasher.

impl PartialEq for StatisticModelCode

fn eq(&self, other: &StatisticModelCode) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Serialize for StatisticModelCode

fn serialize<S>( &self, serializer: S, ) -> Result<<S as Serializer>::Ok, <S as Serializer>::Error>

where S: Serializer,

Serialize this value into the given Serde serializer.

impl Copy for StatisticModelCode

impl Eq for StatisticModelCode

impl StructuralPartialEq for StatisticModelCode