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Statistical analysis using multistate qualitative variables applied to the human dental morphological traits in the Bronze Age (Granada, Spain, 1300-1500 B.C.)

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The study of dental morphological traits in prehistoric populations is a new method of analysis and allows us to determine important characteristics of different human populations. In this paper we study the dental feature traits proposed by the ASU System (developed by Turner et al. in Arizona State University) by means of an alphanumeric and graphic database recording the dental morphological characteristics and the possible dental diseases (caries, dental wear, etc.). These traits are easily observed, and persist many years in dentally harsh life styles, evolving very slowly and without sex dimorphism. The multivariate data set obtained using the ASU System is defined by means of multistate qualitative variables, and the methodology of statistical analysis is the following: – The MMD test (Mean Measures of Divergence) was developed by Sjovold (1977) to observe the differences between two or more previously established and defined groups by means of multistate qualitative variables. It is also possible to test if existing differences among populations are ethnic, cultural, etc. – A Cluster Analysis algorithm developed by one of the authors (Esquivel1988) that enables us to build a grouping using qualitative multistate variables by means of specific developments in Information Theory established by Claude Shannon. Therefore, it is possible to determine the similarities of dental morphological traits between human groups, and compare these results with other previous information from archaeological data. This methodology has been applied to analyse human genetic diversity using exclusively dental morphological characteristics to determine the diffusion of the culture of the Argar, a prehistoric culture which existed in 1300-1500 B.C. The analysis has been applied to the teeth of 116 subjects belonging to the Argaric culture in the neighbouring settlements of Castellón Alto and Fuente Amarga (Granada, Spain), and the teeth of 58 subjects belonging to the non-Argaric settlement of La Navilla, also 1300-1500 B.C., about 150 Kms. Distant. The results show a biological continuity, endogamy phenomena and genetic drifts. Finally, the study of the maxillar pathology like cavities and dental wear tells us about dental health, food and food preparation. pp. 239-255
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Statistical analysis using multistate qualitative variables
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Archeologia e Calcolatori
15, 2004, 239-255
STATISTICAL ANALYSIS USING MULTISTATE QUALITATIVE VARIABLES
APPLIED TO THE HUMAN DENTAL MORPHOLOGICAL TRAITS
IN THE BRONZE AGE (GRANADA, SPAIN, 1300-1500 B.C.)
1. INTRODUCTION
The study of genetic diversity using dental morphology is recent and
constitutes an element providing a great quantity of information in anthro-
pological investigations. The Arizona State University Dental Anthropology
System uses a set of traits that allows us to measure the presence/absence
dichotomy and obtain replicability of results among observers. The ASU stand-
ard obtains the maximal and the minimal trait expression, and various grada-
tions between these points.
Although the set of traits proposed by the ASU standard is very large,
in this paper we use a subset of them, due to the characteristics shown by the
archaeological remains, using the following criteria (TURNER, NICHOL, SCOTT
1991):
the selected traits are the most easily and reliably observed;
they persist for many years even if the subject had a harsh lifestyle. This
case is the most usual in archaeological samples;
most traits have low or no sex dimorphism. This feature is very important
because usually it is very difficult to obtain prehistoric archaeological re-
mains having sexual distinction.
those traits evolve very slowly and permit a distinct characterization of
very well the populations for affinity studies.
2. THE ASU SIMPLIFIED DENTAL ANTHROPOLOGY SYSTEM
The scoring procedures in the ASU system are focused mainly on the
morphological features of the crowns and roots mainly, having special fea-
tures in function of the type of the root. Since the conditions in which the
archaeological remains appear make it very difficult determine in a reliable
way the degree of the traits, in this paper we propose to use the presence or
absence of each feature to get the minimal and maximal trait representation,
for greater reliability in the information obtained.
These simplified sets of morphological features of the crown and roots
are obtained from the qualitative scoring proposed by TURNER, NICHOL, SCOTT
(1991) and they are focused on upper teeth, mainly showing the following
traits.
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2.1 Crown characters of incisors and canines
The traits used are winging with reference to the upper central incisors
(ENOKI, DAHLBERG 1958; TURNER 1970); Labial Convexity relative to upper
incisors (NICHOL, TURNER, DAHLBERG 1984; SCOTT, TURNER 1997); Shoveling
is relative to upper incisors, canine and lower incisors (HARDLICKA 1920;
DAHLBERG 1956; SCOTT, TURNER 1997); Double-Shoveling occurs in upper
incisors, canine and lower incisors (DAHLBERG 1956); the Interruption Groove
appears in upper incisors (SCOTT, TURNER 1997); the Tuberculum Dentale
feature is present in upper incisors and canines (NICHOL, TURNER 1986); the
Canine Mesial Ridge or Bushman canine is located in upper and lower ca-
nines (MORRIS 1975; SCOTT, TURNER 1997); Canine Distal Accessory Ridge
appears in upper and lower canines (MORRIS 1975; SCOTT, TURNER 1997); the
Peg-Shaped character occurs in the upper lateral incisors (SCOTT, TURNER 1997);
Congenital Absence character appears in the upper lateral and lower central
incisors (MONTAGUE 1940; SCOTT, TURNER 1997); the Canine Root Number is
present in lower canines (SCOTT, TURNER 1997).
2.2 Crown characters of premolars
The traits studied include the Double-Shoveling located in the first premo-
lar (DAHLBERG 1956); the Premolar Mesial and Distal Accessory Cusps occurs
in the upper premolars (TURNER 1967); Tricusped Premolars is a very rare trait
located in the upper premolars (SCOTT, TURNER 1997); the Distosagittal Ridge
or “Uto-Aztecan Premolar” appears in the first upper premolar (MORRIS et al.
1978); Enamel Extensions are present in the upper premolars (PEDERSEN 1949);
Premolar Root Number is measured in the upper premolar (SCOTT, TURNER
1997); the presence of Odontome occurs in the upper and lower premolars
(PEDERSEN 1949; ALEXANDARSEN 1970; SCOTT, TURNER 1997); Congenital Ab-
sence character appears in the upper lateral and lower second premolars
(MONTAGUE 1940; SCOTT, TURNER 1997); Tomes’ Root is present in lower first
premolars (TOMES 1923; SCOTT, TURNER 1997).
2.3 Crown characters of molars
The traits considered are the Metacone and the Hypocone characters
located in the upper molars (DAHLBERG 1951; TURNER 1979); Cusp 5 or
Metaconule trait appears in upper molars (HARRIS 1977); the Carabelli’s
trait appears in the upper molars (DAHLBERG 1956; SCOTT, TURNER 1997);
the Parastyle character is located in upper molars (BOLK 1916; SCOTT, TURNER
1997); Enamel Extensions are present in the upper molars (PEDERSEN 1949);
the Upper Molar Root Number is measured in the upper molars (SCOTT,
TURNER 1997); the Peg-Shaped molar character occurs in the upper third
molar (SCOTT, TURNER 1997); Premolar Lingual Cusp Variation is very sen-
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sitive to wear and occurs in the lower premolars (PEDERSEN 1949; KRAUS ,
FURR 1953; SCOTT, TURNER 1997); the Congenital Absence character ap-
pears in the upper lateral and lower third molars (MONTAGUE 1940; SCOTT,
TURNER 1997); the Anterior Fovea trait is located in the lower first molar
(HARDLICKA 1924; SCOTT, TURNER 1997); the Groove Pattern feature ap-
pears in the lower molars with three scorings: X, Y and + (HELLMAN 1928;
JORGENSEN 1955; SCOTT, TURNER 1997); the Cusp Number scores the cusp
number in the lower molars (GREGORY 1916; SCOTT, TURNER 1997); Deflect-
ing Wrinkle appears in lower first molar (SCOTT, TURNER 1997); Distal Trigo-
nid Crest occurs in the lower molars (HARDLICKA 1924; HANIHARA 1961;
SCOTT, TURNER 1997); Protostylid character is located in the lower molars
(DAHLBERG 1956; SCOTT, TURNER 1997); Cusp 5, Cusp 6 and Cusp 7 are
located in lower molars (SCOTT, TURNER 1997); Lower Molar Root Number
is present in lower molars (TURNER 1971; SCOTT, TURNER 1997).
This set of morphological features is stored by means of a database
developed in ACCESS database management using a form of data recording
that includes the set of simplified morphological dental features (Fig. 1).
Fig. 1 – The ASU system. Simplified database.
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This database form developed is easy to use, and includes the list of the
teeth (see diagram) and the list of the jaws, and features verification fields to
avoid possible mistakes. It also includes other optional information about the
archaeological site: the settlement key (in Spain this codification is composed
of two alphabetical characters belonging to the province, two alphabetical char-
acters belonging to the town, and a number (with three digits) corresponding
to the settlement in the town, the place-name, the chronology and the UTM
coordinates of the settlement. This information is important for comparing
two or more different settlements, but it is possible to save each archaeological
site data set in an independent file and merge the files later.
The information recorded in the database can be exported to another soft-
ware like EXCEL, SPSS, MATLAB, the interchange format ASCII, and so. This
data set file can be analysed by means of standard statistical procedures, MATLAB
routines, etc., or can be written using WORD or other software packages.
3. THE MMD (MEDIAN MEASURES DIVERGENCE) METHOD
The previous method allows us to convert the variables in dicotomized
qualitative variables, and it makes the assumption that there is only a single
genotype for any specific trait, and that, when asymmetry is present, the
antimere exhibiting the greater degree of trait expression is the more accu-
rate indicator of the genotype. The score used is the highest grade of expres-
sion observed between the two sides (TURNER, NICHOL, SCOTT 1991). How-
ever, the statistical MMD method is established for general qualitative
multistate variables, and not presence/absence variables only.
The statistical procedure assumes that the variables are independent
variables with no correlation between them, and each one follows a binomial
distribution because the global population is very large. Then, for each trait
the expectation of the proportion p and the variance of p is:
being P the proportion of the trait in the total population (an unbiased esti-
mator of P, that has the least variance and is a sufficient estimator) and N is
the number of individuals in the sample. However, if N is small for a variable
there may be great discrepancies between p y P, and all the proportions do
not have equal importance. Therefore, it is essential to transform the propor-
tion p in a new variable with no dependent variance of the population pro-
portion P; this new quantitative variable is obtained using the inverse sine
transformation, measured in radians, by means of the formula (GREWAL 1962):
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This variable has the advantage that the variance is approximately 1/N
instead 820.7/N (this is the variance obtained using the more usual transfor-
mation Θ = arcsin
p) (BERRY, BERRY 1967; SJØVOLD 1973).
The test of differences between two populations was established by
BERRY (1963) according to:
under the hypothesis that there is no genetic difference between the popula-
tions compared, the proportions p1 and p2 in two samples must be equal
apart from sampling fluctuations. Then, the difference Ø1 - Ø2 is approxi-
mated by a normal distribution with variance (1/N1 + 1/N2), and the statistic
is distributed by means of a normal distribution N(0,1). Therefore, the ex-
pression
follows a distribution, and the expression
will be approximately distributed according to . And it can be
demonstrated (SJØVOLD 1973) that the expectation of X is E(X)=0 and the
variance of X is
The Mean Measure Divergence between the samples 1 and 2 using the
mean of X extended to all traits is defined by:
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being:
θ1i=angular transformation of the proportion p1 of elements in the sample 1
for the trait i;
θ2i=angular transformation of the proportion p2 of elements in the sample 2
for the trait i;
N1i=number of elements in the sample 1 having no missing the trait i;
N2i=number of elements in the sample 2 having no missing the trait i;
V=number of traits that can be evaluated in the samples.
The variance of MMD is obtained by means of the expression (BERRY,
BERRY 1967):
The p1i and p2i proportions can take extreme values distorting the an-
gular transformation. In this case the previous values must be replaced by the
following values (SJØVOLD 1973):
– if the proportions are near 0 we must take and
– if the proportions are near 1 we must take and
The MMD value is distributed according to , but it is
usual to use the following rule proposed by BERRY, BERRY, UCKO (1967):
if is bounded for each i, the MMD is asymptotically normally dis-
tributed and is significant at the 0.05 probability level when the MMD is
twice than its standard deviation (SJØVOLD 1973; SJØVOLD 1977; AL-ABBASY,
SARIE 1997; BAILEY 2000).
4. THE CLUSTER ANALYSIS ALGORITHM
Cluster analysis constitutes a very important statistical method to de-
tect grouping in a data set, and many techniques are developed to make
classifications, groups of objects, etc., based on quantitative variables. How-
ever, an important part of the archaeological data is defined by means of
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qualitative variables with several states, but there are no procedures adapted
for grouping these data except for presence/absence data (SNEATH, SOKAL 1973;
ROMESBURG 1984; KRZANOWSKI 1988).
The methods of analysis for qualitative variables usually codify each
state of each variable as a new presence/absence variable, loosing the linkage
between the states in the same variable. This problem has been approached
by several scientific theories such as image recognition, string of symbols
recognition, database management, archaeological pattern recognition of in-
complete data, etc. (MICHALSKI, STEPP 1983; BEN-BASSAT, ZAIDENBERG 1984;
CHIU, WONG 1986; ESQUIVEL 1988; FUKUNAGA 1991).
According to the Shannon theory, in a mathematical communication
model the information is determined by a statistic parameter associated with a
probability scheme, and it must indicate a measure related to the uncertainty
according to the occurrence of a particular message in a set of messages:
We propose that the information carried out by the xik state with ex-
perimental probability pik and ni number of states, and the associated entropy
to the Xi variable are defined as:
The entropy H(Xi) minimizes the influence of the rare cases; but
this influence is very important to study the association between elements
because: «the agreement in rare states is less probable that the agreement
between frequent states and it must be more valued» (SNEATH, SOKAL 1973).
The total entropy of the Xi (ESQUIVEL 1988) is accord to the previous
ideas:
The total entropy D(X i) measures the byass or distortion that pro-
duces a non regular variable in the space of elements.
Being G={A1, A2, ... An} the set of elements defined by the set of quali-
tative multistate variables V={X1, X2, ... Xv}, and ni the number of states of
variable Xi. Each element has linked a mathematical object defined by the n-
pla of measures (DUBOIS, PRADE 1980) m(Ai)={(m1(Ai), m2(Ai), ... mv(Ai)},
k=1,...,v and i=1,...,n, being mk(Ai)=xkj if j is the index of the state of vari-
able Xk that is in Ai. The set of mathematical objects defined by this proce-
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dure is named the “pattern space” S, and using pi(A) as experimental fre-
quency of the xij state, the distortion that produces an element is defined by
the total uncertainty originated by that element in the pattern space and is
formuled by the mathematical expression:
The interaction between elements determines the clustering by means of
the similarity characteristics of each one. Using a similar terminology to the
physical sciences and used by the pattern recognition theory, the information
measurement of attraction between elements will decide that units can be clus-
tered and the intensity of clustering. The attraction measure between two ele-
ments must reveal the common information in the variables shared by them,
while the dissimilarity must quantify the difference between them.
These concepts need the previous definitions:
Common information between two elements. Is defined according to the
mathematical set intersection
Joint information between two elements. Is defined according to the math-
ematical set union
The information values allowed by the common and the joint informa-
tion verify the basic relations established by PAL, DUTTA MAJUMDER (1985) to
quantify the degree of fuzzyness of a data set.
This theorem allows us to obtain the joint information provided by the
elements of the group Gn={A1, A2, ..., An} according to the boolean logic
rules (ESQUIVEL 1988; ESQUIVEL 1999):
In a space pattern, the study of the relations needs a parameter that
quantifies the distance between groups of elements, or conversely a similarity
measure because the basic relation is d(A,G)=1-S(A,G) (in this paper we use
a similarity measure). In the case of similarity between two elements, the
affinity measure is the common information between them. The relation be-
tween the affinity function and the information of elements is established by
the following expression (ESQUIVEL 1988; ESQUIVEL 1999):
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This definition verifies the properties established by BACKER, JAIN (1981)
that must verifiy each affinity measures:
1) the affinity measure element-group should not be smaller if the element is
a member of the group that if it is not contained in him;
2) the affinity will be near 0 when the element is spurious to the group;
3) the affinity will be an absolute maximum if the group is constituted by an
single element having the same localization that the previous element.
Two basic forms are possible to establish a similarity measure:
This measure verifies the conditions established by BACKER, JAIN (1981)
and only quantifies the uncertainty provided by the states that appear in all
and each one of the elements of the groups.
The S2 measure doesn’t verify the conditions imposed by Backer and
Jain since it takes into account all the occurrences among the elements of the
groups, and therefore the uncertainty is added to the total value increasing.
Also, it is less strict than the previous measure.
5. DATA SET AND RESULTS OF ANALYSIS
The data have been obtained from the remains of burials belonging to
three contemporary settlements belonging to different cultures and with great
geographic proximity (about 150 km). The Castellón Alto and the Fuente
Amarga settlements are prototypes of the Argaric culture and they are lo-
cated in Galera and Huéscar (Granada, Spain), on the left bank of the river
Galera, on a steep terraced hill. In the construction of the cottages, the in-
habitants took advantage of the natural terraces. Their main cultural charac-
teristics are the production of a special pottery, a diet based on agriculture,
and the burial of the inhabitants with their trousseau under the houses or
inside tiny caves in the walls of the hill.
The La Navilla settlement is a megalithic dolmen with multiple burial
that contains the remains of 54 human bodies, most conserved in an incom-
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plete state. It is contemporary to the other locations and it is located in the
right bank of the river Cacín. Culturally it is quite different from the Castellón
Alto and Fuente Amarga settlements since it belongs to the Copper Age. There
are no burials under the cottages or in the little caves, and they were stock-
breeders but not farmers; however the pottery found in the burials is an
Argaric typology, maybe due to the geographical proximity and to
contemporary acculturation phenomena that occured.
The data set is composed of the teeth of 54 individuals in the mega-
lithic cemetery of La Navilla and of 114 individuals, generally incomplete,
found in the Argaric settlements of Castellón Alto and Fuente Amarga in a
good conservation state. The dental morphological variables have been stud-
ied according to the methodology of the ASU system and other pathologies
have been analyzed (caries, toothloss before death and dental waste).
We carried out previous morphological studies to obtain the distribu-
tion of the different characters of the maxillary and the jaw for sides and sex,
to determine that differences do not exist due to the sex or the laterally using
χ2 tests. We have distinguished males, females and undetermined (all non
adults and those older than 20 years for whom it has not been possible to
determine the sex are included in this category).
In all the cases the non existence of statistically significant differences
with a significance level p <0.05 was determined, which is in agreement
with the results obtained in previous works (TURNER, NICHOL, SCOTT 1991;
HILLSON 1996; SCOTT, TURNER 1997), indicating that dental morphological
characters usually exhibit a high grade of symmetry. In some studies already
completed, the agreement between both sides exceeds 95% and only 7% of
fellows sample some asymmetry, generally in expression grades (SCOTT, TURNER
1997).
Since many characteristics are not represented and in order to assign
greater value to the possible differences than to the similarities, 36 features
have been selected among those whose frequencies diverge more (see Tables
1 and 2). The values of the MAD and their standard deviation, as much for
the maxillary one as for the jaw, do not reflect statistically significant differ-
ences at p<0.05 significance level. In this study we have distinguished be-
tween the maxillary and the jaw cases to obtain greater detail in the results;
also most of the characteristics of the jaw do not appear in the maxillary.
The global MMD value for traits in maxillary is 0.184 with standard
deviation Ã=0.059, showing no statistically significant differences between
the Argaric settlements and the non-Argaric Navilla settlement, with a sig-
nificance level p<0.05 because the MMD value is not twice its standard
deviation. Also, the analysis of the jaw provides a global MMD value 0.125
with standard deviation Ã=0.038, showing no statistically significant differ-
ences between the Argaric settlements and the non-Argaric Navilla settle-
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ment, with a significance level p<0.05 because MMD<2 Ã (SJØVOLD 1973;
SJØVOLD 1977; AL-ABBASY, SARIE 1997; BAILEY 2000).
The analysis using the MMD test indicates that significant differences
do not exist for the total of dental variables between the sample of the Navilla
and that of the Argaric settlements in Galera. Although variables with more
differences were selected for this analysis, the result has been negative. Ac-
cording to the historical data, the two population samples studied descend
biologically from the populations that inhabited East Andalucia in the Cop-
per Age and, therefore, they do not differ from each other, too very little
time has passed for evolutionary phenomena to occurr. Some of these traits
present significant differences and could correspond to endogamy phenom-
ena and/or drift genetics, which demonstrates that, inside the generality, each
group presents some distinctive characteristics.
In general, both populations, as well as those of the Neolithic and Cop-
per Age in Andalucia (GALLARDO 2001), although among them some small
differences appear, fit the general profile that defines the populations from
Europe and Western Asia for dental morphological variables.
These measures get very good results from clustering a data set defined
by qualitative multistate variables. The previous cluster analysis algorithm
has been applied to the data set and confirms the results provided by the
MMD test, i.e., there is no separation between the Argaric and non-Argaric
populations, and the teeth of both populations appear mixed in the groups
and subgroups obtained in the dendrogram tree.
Traits MMD
Canine Distal Accessory Ridge 0.290
Premolar Lingual Cusp Variation P20.039
Anterior Fovea 0.170
Groove Pattern X M20.232
Groove Pattern Y M10.084
Groove Pattern X M3-0.005
Cusp Number M10.084
Cusp Number M2-0.009
Distal Trigonid Crest M20.396
Protostylid M10.058
Protoslylid M30.021
Protostylid M3-0.076
Cusp 5 M2-0.009
Cusp 5 M30.341
Cusp 7 M10.232
Canine Root Number -0.011
Congenital Absence I10.170
Congenital Absence M30.238
Tab. 1 – MMD results for the present traits in the maxillary between the Navilla settlement and
the Argaric settlements.
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Due to the great quantity of data available, in this paper the results
described are those obtained when applying the algorithm to the teeth of the
maxillary. The categories used have been the tooth type (M1, M2 and M3)
and those specific variables of the maxillary ones: Metacone, Hypocone,
Cusp 5, Carabelli’s Trait, Parastyle, Enamel Extensions and Root Number.
The teeth numbered 1-25 are the non-Argaric. The dendrogram shows the
following results (Fig. 2):
There are no isolated groups for Argaric and non-Argaric settlements us-
ing the teeth of the maxillary.
Each group is composed of teeth belonging to both cultures, without dis-
tinction between them.
There is not a specific typology that allows us to determine if a tooth
belongs to one or another culture.
6. CONCLUSIONS
In this work we have studied the remains of maxillary and jaws belong-
ing to 168 individuals with a total of 1313 pieces belonging to the multiple
megalithic graves of La Navilla (necropolis of the Pantano de los Bermejales,
Granada) and of the Argaric settlements of Castellón Alto and Fuente Am-
arga (near Galera, Granada), sites that are near to each other geographically.
This material has been analyzed on the basis of the dental morphological
characteristics using the ASU (Arizona State University) system.
Tab. 2 – MMD results for the present traits in the jaw between the Navilla settlement and the
Argaric settlements.
Traits MMD
Canine Distal Accessory Ridge 0.290
Premolar Lingual Cusp Variation P20.039
Anterior Fovea 0.170
Groove Pattern X M20.232
Groove Pattern Y M10.084
Groove Pattern X M3-0.005
Cusp Number M10.084
Cusp Number M2-0.009
Distal Trigonid Crest M20.396
Protostylid M10.058
Protoslylid M30.021
Protostylid M3-0.076
Cusp 5 M2-0.009
Cusp 5 M30.341
Cusp 7 M10.232
Canine Root Number -0.011
Congenital Absence I10.170
Congenital Absence M30.238
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Fig. 2 – Dendrogram obtained by means of cluster analysis algorithm using qualitative multistate variables.
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Although the study was very complicated due to the high grade of
deterioration of the Argaric teeth, and the mixed disposition of the material
of La Navilla, satisfactory results have been obtained.
The previous analyses do not show statistically significant differences
between jaw and maxillary or between sexes, which coincides with the char-
acteristics of the phenotypic distribution of the dental morphological vari-
ables. Therefore, the morphological features of the ASU system are an excel-
lent indicator for the comparison between biological populations that are
not affected by environmental factors such as diet, disease, etc.
The application of the MMD test of differences shows that statistically
significant differences do not exist among contemporary and very near geo-
graphically Argaric and non-Argaric populations in Granada, showing that
the people studied belong to the same biological population. Therefore, any
differences among these locations will be due to cultural factors, etc.
These results have been confirmed by means of the application of an
algorithm of cluster analysis developed to use multistate qualitative variables,
showing that independent groups do not exist between the Argaric and non-
Argaric populations studied.
The trait frequencies of the ASU system indicate that the populations
studied belong biologically to that which SCOTT and TURNER (1997) have de-
fined as populations from Western Eurasia. That is to say, they form part of
the group of populations from Europe, North Africa and Southwest Asia.
Some characteristics present different frequencies from those of West-
ern Europe, but we cannot determine if they are or are not characteristic
features of Mediterranean populations, since the moment the number of stud-
ies of this type in the North valley is very small and therefore a biological
characterization of these populations has not been made based on their den-
tal morphological variables.
The frequencies obtained are very similar to the signal ones recorded
by GALLARDO (2001) for the populations of the Neolithic Age and the Copper
Age in Granada. Therefore, it is possible to affirm that a biological continu-
ity exists in the region from the Neolithic to the Bronze Age.
JOSÉ ANTONIO ESQUIVEL
Departamento de Prehistoria y Arqueología
Instituto Andaluz de Geofísica
Universidad de Granada
IHAB AL OUMAOUI
Departamento de Prehistoria y Arqueología
Universidad de Granada
SILVIA JIMÉNEZ-BROBEIL
Departamento de Ciencias Morfológicas
Laboratorio de Antropología Física
Universidad de Granada
Statistical analysis using multistate qualitative variables
253
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ABSTRACT
The study of dental morphological traits in prehistoric populations is a new method
of analysis and allows us to determine important characteristics of different human popu-
lations. In this paper we study the dental feature traits proposed by the ASU System
(developed by Turner et al. in Arizona State University) by means of an alphanumeric and
graphic database recording the dental morphological characteristics and the possible dental
diseases (caries, dental wear, etc.). These traits are easily and reliable observed, and per-
sist many years in dentally harsh life styles, evolving very slowly or without sex dimor-
phism.The multivariate data set obtained using the ASU System is defined by means of
multistate qualitative variables, and the methodology of statistical analysis is the following:
The MMD test (Mean Measures of Divergence) was developed by SJOVOLD (1977) to
observe the differences between two or more previously established and defined groups
by means of multistate qualitative variables. It is also possible to test if existing differ-
ences among populations are ethnic, cultural, etc.
A Cluster Analysis algorithm developed by one of the authors (ESQUIVEL 1988) that
enables us to build a grouping using qualitative multistate variables by means of specific
developments in Information Theory established by Claude Shannon. Therefore, it is
possible to determine the similarities of dental morphological traits between human
groups, and compare these results with other previous information from archaeological
data.
This methodology has been applied to analyze human genetic diversity using ex-
clusively dental morphological characteristics to determine the diffusion of the culture of
the Argar, a prehistoric culture which existed in 1300-1500 B.C. The analysis has been
applied to the teeth of 116 subjects belonging to the Argaric culture in the neighbouring
settlements of Castellón Alto and Fuente Amarga (Granada, Spain), and the teeth of 58
subjects belonging to the non-Argaric settlement of La Navilla, also 1300-1500 B.C.,
about 150 Kms. distant. The results show a biological continuity, endogamy phenomena
and genetic drifts. Finally, the study of the maxillar pathology like cavities and dental
wear tells us about dental health, food and food preparation.
J.A. Esquivel, I. al Oumaoui, S. Jiménez-Brobeil
256
© 2004 - All’Insegna del Giglio s.a.s. - www.edigiglio.it
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Book
Full-text available
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  • Pal S K Dutta
PAL S.K., DUTTA MAJUMDER D.D. 1985, Fuzzy Mathematical Approach to Pattern Recognition, New Delhi, Wiley Eastern.